Analysis and Optimization of Ponybuy's Purchasing Categories Using Spreadsheets
As an e-commerce platform specializing in overseas purchasing services, Ponybuy relies on data-driven decisions to refine its product catalog. This article explores how to analyze Ponybuy's purchasing category data—such as sales share, growth rate, and profitability—using spreadsheets, and how to derive actionable optimization strategies.
1. Data Collection and Spreadsheet Analysis
To begin, we structure key metrics into a spreadsheet (e.g., Google Sheets or Microsoft Excel), including:
- Category Sales Share:
- Growth Rate (YoY/MoM):
- Profit Contribution:
- Inventory Turnover:
Example Table Structure:
Category | Sales Share (%) | Growth Rate (MoM) | Profit Margin (%) |
---|---|---|---|
Skincare | 35% | +12% | 45% |
Electronics | 20% | -5% | 15% |
2. Aligning Data with Market Trends
Cross-reference internal data with external trends:
- Rising demand for sustainable brands in fashion (e.g., thrifted luxury).
- Tech gadgets with AI features gaining traction among young consumers.
- Declining interest in generic cosmetics due to market saturation.
Use spreadsheet charts (e.g., trendlines, pie graphs) to visualize gaps between current offerings and market opportunities.
3. Category Optimization Strategy
Phase Out Low-Performance Categories:
- Discontinue electronics with sub-10% profit margins unless they serve as customer acquisition tools.
- Reduce inventory for slow-growing categories (e.g., traditional supplements).
Introduce High-Potential Categories:
- Add niche subcategories (e.g., K-beauty "clean" skincare based on search trends).
- Partner with trending brands in "DTC wellness" (e.g., menstrual care tech).
Dynamic Rebalancing:=IF(Growth_Rate<5%,"Review","Keep")) to flag categories needing quarterly reassessment.
4. Implementation and Monitoring
Create a dashboard to track KPIs post-optimization, such as:
- Gross Merchandise Value (GMV) per category.
- Customer retention rates for new categories.
Adjust inventory procurement based on real-time spreadsheet updates linked to POS systems.