This page contains the spreadsheets and research referenced in my YouTube category breakdowns.

All data is pulled from recent sold listings and is meant to help resellers understand where real demand exists, not just which brands are popular.

This is not a BOLO list.
It is sell-through driven research designed to improve buy or pass decisions at the thrift store.

Each spreadsheet reflects the data available at the time of the video and is shared so you can study the patterns yourself.

Available Research

Men's Pants Sell-Through Data Includes brand-level active vs sold counts, 90-day sell-through rates, average sale prices, and supply pressure scores across 20+ men's pants brands. Focused on technical and workwear velocity, lifestyle brand trend signals, and category indicators like BOLO shelf life, brands on the clock, and trap brand flags. Download: https://docs.google.com/spreadsheets/d/1UJpOBUkxXUeIhF4zyKx9ykzF6tzZA9zUqDXyb4W7MSk/edit?usp=sharing

Levi’s Men’s Jeans Sell-Through Data
Includes model-level active vs sold counts, 90-day sell-through rates, and average sale prices across the core Levi’s lineup.
Focused on fit-level velocity, USA and vintage demand multipliers, and tab signals like Big E, Selvedge, LVC, and White Oak Cone.

Download:

Women’s Tops Sell-Through Data
Includes brand-level active vs sold counts, 90-day sell-through rates, and pricing ranges.
Focused on demand multipliers like size, material, premium lines, and country of origin.

Men’s Jeans Sell-Through Data
Brand-level analysis of sell-through velocity and average pricing across the men’s jeans category.

Women’s Jeans Sell-Through Data
Sell-through and pricing breakdowns focused on demand strength, not hype brands.

Women's Dresses Sell-Through Data

70+ dress brands with active vs sold counts, 90-day sell-through, average sale prices, and demand multipliers for plus size, material, and length.

How to Use This Research

Spreadsheets are best for learning patterns over time.

They help answer questions like:

  • Which categories drain inventory fastest

  • Where pricing actually clusters

  • When size, material, or line matter more than brand

In the thrift store, this level of analysis is not always practical in real time.
That is why I built BrandScout, to apply this same logic faster while sourcing.

If you are here to study the data, start with the spreadsheets.
If you want to apply it consistently without slowing down, BrandScout exists for that purpose.

This library will be updated as new category breakdowns are published.

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