Not every product justifies the same level of tracking detail. Understanding the best products to track using a lovegobuy spreadsheet helps you allocate your administrative time where it generates the highest return. High-value items, variable-cost items, and fast-moving inventory deserve meticulous tracking. Low-margin, fixed-cost commodities need less attention. This guide breaks down tracking priorities by product category and explains how to customize your spreadsheet columns for each type.
High-Priority Tracking Categories
Certain product categories inherently require more tracking complexity because they involve more variables. Sneakers, for example, often have size-related price variations, authentication concerns, and significant resale value differences between colorways. A hoodie might have a fixed cost and predictable margin, but a limited-edition sneaker could see its resale value fluctuate by fifty percent based on release timing and market demand.
Items purchased in bulk for wholesale redistribution also demand rigorous tracking. When you buy twenty identical jackets, a single tracking number covers the entire shipment. But if those jackets have different sizes destined for different customers, you need row-level detail to assign the correct items to the correct orders downstream.
Category Tracking Intensity Guide
| Product Category | Track Level | Key Columns | Why |
|---|---|---|---|
| Sneakers / Shoes | High | Size, SKU, Auth | Size affects value, fakes exist |
| Hoodies / Sweaters | Medium | Size, Weight | Shipping cost varies by weight |
| T-Shirts | Low-Medium | Size, Print | Usually consistent margins |
| Jackets | Medium | Size, Material | High shipping, seasonal demand |
| Headwear | Low | Style | Low cost, simple shipping |
| Accessories | Medium | Type, Material | Wide margin variation |
| Sets / Outfits | High | Components, Sizes | Multiple items per listing |
| Jerseys | Medium | Player, Size, League | Seasonal, player-dependent |
Customizing Columns by Product Type
Your lovegobuy spreadsheet should adapt to what you sell. For sneakers, add columns like Authenticated (yes/no), Box Condition, and Resale Platform. For jackets, add Material and Season columns because a puffer jacket and a windbreaker have completely different shipping weights and storage needs. For accessories, add a Gift-Ready column if you sell through platforms where packaging presentation affects reviews.
Do not create a one-size-fits-all monster spreadsheet with thirty columns where only five apply to each item. Instead, use the base template for common data and create category-specific tabs within the same workbook. This modular approach keeps each view clean while preserving the ability to generate consolidated reports across all categories.
Tracking Profit by Category
One of the most valuable insights a spreadsheet provides is category-level profitability. You might discover that T-shirts generate a consistent 35% margin with almost no customer service issues, while sneakers average 55% but require three times as much communication and authentication effort. When calculated as profit per hour of your time, the T-shirts might actually be more lucrative.
Use SUMIF formulas to calculate total profit by category on your summary dashboard. Update this analysis monthly. Over time, the data will guide your purchasing decisions more effectively than fashion trends or supplier recommendations. The numbers reveal what actually works for your specific business model and customer base.
Seasonal and Trend-Based Adjustments
Fashion is seasonal, and your tracking should reflect that. Add a Season column to flag items as Spring, Summer, Fall, or Winter. When reviewing your dashboard in October, filter for Winter items to see if your cold-weather inventory is sufficient. When Spring arrives, check your Summer stock levels and place orders before demand spikes increase both product costs and shipping rates.