DEDavid Erfanian
Case Study

EFFY StyleRecommender

Merchandise Analytics and Inventory Recommendation Platform

A planning platform for evaluating sales, inventory, profitability, product movement, allocation, and replenishment opportunities.

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Project overview

I built an application that centralizes those signals, provides searchable and drillable planning views, ranks recommendations, and produces structured Excel and CSV outputs for existing business processes.

My roleLead designer and full-stack developer
TechnologyPython · Flask · SQL Server · pandas · openpyxl · xlsxwriter · JavaScript
IntegrationsSales history, inventory signals, product images, Excel and CSV reporting
ResultConsolidated repeatable planning analysis and ranked recommendations across more than 200 retail locations.
The Context

Business challenge

Planning teams repeatedly rebuilt store, style, sales, inventory, margin, recency, and allocation analysis across spreadsheets and disconnected reports.

The Build

Solution and capabilities

I built an application that centralizes those signals, provides searchable and drillable planning views, ranks recommendations, and produces structured Excel and CSV outputs for existing business processes.

  • Sales and inventory analysis by store, fleet, style, category, vendor, and period
  • Sell-through, units, margin, AUR, cost, recency, and movement metrics
  • Ranked allocation and replenishment recommendations
  • Store and style drilldowns with product-image context
  • Open-order and planning reports
  • Automated downloadable Excel and CSV outputs
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