Marie Camara | BI Analyst

Industry: Cosmetics

Role: Data Analyst

Business Problem

Cosmetics brands operate in a highly competitive market where consumer preferences are shaped by multiple factors (product performance, packaging, pricing, and in-store experience).

Companies often struggle to clearly identify what truly drives purchase intention and willingness to pay, leading to suboptimal product positioning and missed revenue opportunities.

Objectives

• Identify key drivers of purchase intention across product, packaging, and brand dimensions
• Analyze consumer behavior across demographics, product categories, and retail channels
• Evaluate the impact of packaging type and brand tier on willingness to pay
• Provide data-driven, actionable recommendations to optimize product strategy, pricing, and in-store execution.

Methodology and Tools Used

A structured end-to-end analytics pipeline was implemented, from data preparation to insight delivery through an interactive dashboard.

• Data Collection: Synthetic dataset simulating real consumer research — 400 respondents, 36 variables covering demographics, product testing, packaging perception, pricing, and shopper behavior
• Data Cleaning: Verified data types, ensured consistency across categorical variables (e.g., Gender, Brand Tier, Packaging Type), and validated numerical scales (e.g., Likert scores, WTP)
• Data Transformation: Created calculated columns in Power BI, including age groups, purchase intention categories, willingness-to-pay tiers, and NPS segmentation
• Data Analysis: Developed DAX measures such as Purchase Intention, Net Promoter Score (NPS), Average Willingness to Pay, and segment-level comparisons across packaging types, brand tiers, and product categories
• Data Visualization: Designed a 6-page interactive Power BI dashboard (Executive Overview, Consumer Profile, Product Testing, Packaging & Pricing, Merchandising & Shopper Behavior, Insights & Recommendations) with KPI cards, heatmaps, scatter plots, and advanced filtering
• Tools Used: Microsoft Excel, Power BI, Canva

Key Deliverables

• Fully interactive Power BI dashboard with 6 analytical pages
• KPI framework covering purchase intention, NPS, and pricing metrics
• Segmentation analysis across demographics, packaging types, and retail channels
• Consultant-style insights and strategic recommendations for decision-makers.

Key Insights

• Premium packaging significantly outperforms standard options in perceived quality, luxury, and consumer trust
• Efficacy perception is the strongest driver of purchase intention, outweighing purely aesthetic factors
• Low customer advocacy driven by high detractor rate (56%)
• Consumers are willing to pay a substantial premium for high-end packaging, with a clear pricing gap vs standard products
• Specialty and department stores generate higher engagement (longer browse time) and stronger impulse purchase behavior
• Eco-friendly packaging resonates strongly with younger consumers, driving higher trust and brand advocacy despite lower willingness to pay
• Skincare products lead in efficacy and trust, while fragrance shows strong appeal but weaker conversion to purchase.

Recommendations

• Invest in premium packaging for high-value product lines to maximize perceived value and willingness to pay
• Lead with efficacy messaging (clinical results, ingredient transparency) to drive conversion
• Adopt a tiered packaging strategy (Premium, Eco-friendly, Standard) to target distinct consumer segments
• Prioritize high-engagement retail channels (specialty and department stores) for product launches and in-store activations
• Leverage eco-conscious positioning for younger segments to strengthen brand trust and long-term loyalty
• Optimize in-store conversion for fragrance products through experiential strategies (testers, guided selling, trial formats)