Weekly Seasonal Collection Performance Analysis

Track and analyze the performance of current seasonal collections across key metrics including sell-through rates, margins, and customer satisfaction, focusing on identifying trends and opportunities for optimization across product categories.

Report Objective

Monitor and evaluate the performance of seasonal collections across categories, focusing on sell-through rates, margins, and customer feedback to inform product development and inventory management decisions. This weekly analysis helps identify successful styles and opportunities for improvement in future collections.

Category Performance Metrics

Analysis of sell-through rates and margins across product categories

Questions to Consider:

2024-03-012024-04-012024-05-01week_date62.0%64.0%66.0%68.0%70.0%72.0%sum(sell_through_rate) vs. categorysum(sell_through_rate)categoryHow are Sell-Through Rates Trending by Category?Womenswear and Accessories showing strongest sell-through performance
  • Which categories are showing consistent sell-through improvement?

  • Are there seasonal patterns in category performance?

  • How do sell-through rates compare to historical averages?

  • Which categories maintain the healthiest margins?

  • How do margins correlate with sell-through rates?

  • Are there opportunities for margin improvement in specific categories?

WomenswearMenswearAccessoriesFootwearJewelrycategory0.0%200.0%400.0%600.0%800.0%sum(avg_margin)sum(avg_margin)Category Margin AnalysisMargin variations indicate optimization opportunities across categories

Style-Level Analysis

Detailed performance metrics for individual styles including sales volume and customer satisfaction

Questions to Consider:

Leather ToteSlim Fit JeansClassic T-ShirtCashmere Sweaterstyle_name05,00010,00015,00020,00025,000sum(units_sold)sum(units_sold)Top Performing Styles by Units SoldKey styles driving significant volume across collections
  • What common attributes do top-selling styles share?

  • How does sales volume correlate with customer ratings?

  • Are high-volume styles maintaining healthy margins?

  • What is the correlation between ratings and returns?

  • Which styles maintain high ratings with low returns?

  • Are there common issues in highly returned items?

5.010.015.020.025.0sum(customer_rating)5.0%10.0%15.0%sum(return_rate)Style Performance: Returns vs. Customer RatingsIdentifying relationship between customer satisfaction and returns

Areas for Additional Focus