Boutique Apparel Analytics Dashboard: Inventory Refinement & Cross-Selling Insights
Project Objective
I will design and implement an analytics dashboard that enables the boutique apparel chain to refine inventory decisions based on style preferences, understand customer purchasing behavior, and enhance cross-selling opportunities across urban and suburban regions. The dashboard will transform transactional and product data into actionable insights that support inventory optimization and targeted sales strategies.
Key Dashboard Goals
The dashboard will provide comprehensive analytics for:
1. Inventory Performance
Monitor product movement by style, category, and region
Identify fast-moving vs. slow-moving items
Detect inventory aging and stock turnover rates
2. Customer Buying Behavior
Analyze how different customer segments purchase by product type, region, channel (in-store vs. online), and time period
Track repeat purchase patterns and customer loyalty
3. Cross-Selling and Product Affinity
Identify product combinations frequently bought together
Recommend targeted cross-selling opportunities based on co-purchase patterns
Use association analysis to find high-value product bundles
These analytics elements ensure the business can support merchandising decisions that reflect customer preferences and maximize revenue per customer.
Essential KPIs & Metrics
The dashboard will clearly display relevant performance indicators:
Inventory & Product KPIs
Total units sold by product style and category
Inventory turnover rate (Sales / Average Inventory)
Stock coverage days (remaining days of inventory at current pace)
Percentage of slow-moving SKUs
Customer & Sales KPIs
Total sales revenue (by region, channel, style)
Average order value (AOV)
Customer segment sales contribution (e.g., new vs. returning)
Top customer cohorts by revenue
Cross-Selling & Affinity Metrics
Lift and support metrics for product co-purchases
Most frequent product pairs or bundles
Cross-sell revenue contribution vs. stand-alone purchases
These KPI definitions are consistent with standard retail analytics practices used for fashion and general retail dashboards.
