Marie Camara | BI Analyst

Analyzing cosmetics consumer behavior

cosmetics

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).