Best Items to Track Using Your Litbuy Spreadsheet

A one-size-fits-all litbuy spreadsheet works for basic tracking, but buyers who specialize in specific categories know that each product type has unique data points. Sneakers need size run data. Jerseys need team and player tracking. Sets need component tracking. Accessories need SKU variant management.

When you tailor your litbuy spreadsheet columns to the specific items you sell most, your tracking becomes dramatically more useful. You can answer category-specific questions instantly rather than piecing together answers from generic data.

Shoes are the most tracked category in fashion buying and for good reason. The resale market for sneakers is enormous, margins can be significant, and size availability directly determines profitability. A shoe-focused litbuy spreadsheet needs columns for every size from US 4 to US 15, colorway, release date, retail price, and resale price by size.

For shoes, the most critical tracking metric is size distribution. Track which sizes sell fastest for each silhouette. Over time, your data will reveal that certain sizes consistently generate higher margins, allowing you to weight your purchasing toward the most profitable size runs.

Hoodies and sweaters are strongly seasonal. A litbuy spreadsheet for this category needs a Season column alongside the standard fields. Track purchase timing relative to season start, because margins on hoodies bought in early fall are typically much higher than those bought in late winter when demand collapses.

Color is a critical variable for hoodies. Neutral colors like black, grey, and cream typically sell faster and at higher margins than bold colors. Your litbuy spreadsheet data will confirm this pattern within a few buying cycles.

Accessories often have the most SKU variation of any category. A single accessory supplier might offer a hat in twelve colors, five sizes, and three materials. Your litbuy spreadsheet needs to handle this variant explosion without creating hundreds of separate rows.

The solution is a master SKU system where the parent product has one row and variants are recorded in a structured notes field or a linked variant tab. This keeps your main sheet clean while preserving full variant-level detail.

Jersey buying requires tracking attributes that other categories do not need: team, player name, player number, season, and league. A jersey-focused litbuy spreadsheet tracks how player performance affects resale demand and which teams drive the most consistent buying interest.