Unearth is a web‑based marketplace that enables individual sellers to upload photos and details of clothing items for evaluation by nearby thrift stores. The platform matches items to each store’s buying criteria, provides feedback within days, and helps stores acquire higher‑quality, locally sourced inventory while reducing sellers’ time and transportation costs.
Funding
Funding not disclosed
Founders
Product
Problem
Individual sellers often make trips to thrift stores with unsold clothing, facing guesswork about whether the items meet the store’s buying criteria. This results in wasted time, transportation costs, and frequent rejections, while thrift stores struggle to acquire high‑quality, sellable inventory efficiently.
Solution
Unearth offers a web‑based marketplace that lets sellers digitally submit photos and key attributes of their clothing items to nearby thrift stores. Sellers can browse each store’s preferred categories and build a virtual “bag” of items they think will sell, then send the submission for review. Store employees evaluate the submissions and provide feedback within one to two days, enabling sellers to know exactly which pieces to bring in. By pre‑screening inventory, thrift stores receive higher‑quality, locally sourced merchandise faster, reducing the time and effort spent on in‑person triage.
Target Audience
The primary users are individual clothing sellers who want to monetize secondhand items, and thrift store owners or employees seeking a streamlined, local sourcing channel for sell‑through inventory.
Features
- Mobile‑optimized upload interface with fields for size, brand, condition, and photos of each item
- Store‑specific preference pages that list sought‑after styles, brands, and condition thresholds
- Virtual “bag” builder allowing sellers to assemble and edit a curated selection before submission
- Automated notification system that alerts sellers when a store has reviewed their bag and indicates approved items
- Dashboard for thrift store staff to review submissions, accept or reject items, and communicate directly with sellers
- Matching algorithm that suggests stores most likely to purchase each item based on historical acceptance data
- Secure data handling with encrypted image storage and compliance with standard privacy practices