Lootswap.

Context

Lootswap is a sneaker trading and resale platform. Alongside buying and selling, users trade pairs peer to peer, often with several pairs or cash on one side, so the product has to make each offer easy to read, value, and negotiate.

Customer problem

Peer-to-peer sneaker trading is hard to evaluate. Each trade can involve multiple pairs, cash added on top, and shifting market values by model, colorway, size, and condition. Users need a fast way to understand what they are getting, what they are giving, and whether a trade is fair. Sneaker and fashion buyers need relevant discovery and pricing context. Sellers need efficient listing tools, useful market information, and support for reaching buyers across marketplaces.

What I owned

Product Manager, June 2022–July 2024, Houston. Built a two-sided consumer marketplace from zero through acquisition across iOS, Android, and web. Owned onboarding, listings, search and discovery, checkout, payments, seller tools, fulfillment, and trust & safety.

Strategy & prioritization

Used funnel and behavioral analysis with GA4, UXCam, and Branch to find conversion drop-offs and prioritize the roadmap. More detail on the initial marketplace focus and individual prioritization decisions is still to come.

Constraints & options considered

Capture the decisions around external market prices versus seller flexibility, cross-listing convenience versus inventory consistency, and catalog structure versus fast listing creation. Add the actual constraints and chosen approaches.

Key decisions & why

The three decisions that shaped the core buying and selling experience:

1. 01

   Trade comparison · Make both sides of the trade legible

   Trades can involve multiple pairs and cash on top. A side-by-side offer view shows what you’re getting, what you’re giving, and how the deal is structured.

2. 02

   Value clarity · Turn market data into negotiation context

   Estimated values give both traders a shared reference point, making it easier to judge fairness and negotiate without relying only on instinct.

3. 03

   Trust · Help users evaluate both the deal and the trader

   Trade decisions depend on more than the shoes. Reputation, trade history, and offer transparency help users decide whether to accept, counter, or walk away.

Execution

Launched a StockX-powered Price Guide using live market data to surface resale values and historical pricing by size. Shipped an eBay cross-listing tool that automatically mapped listing photos and product data to eBay. Used GA4, UXCam, and Branch for funnel and behavioral analysis.

Outcome & learning

Structured trade offers, side-by-side estimated values, and trader reputation reduced the ambiguity in peer-to-peer sneaker negotiation. Took the marketplace from zero through acquisition across iOS, Android, and web. The Price Guide improved listing price accuracy and sell-through; eBay cross-listing expanded seller reach and drove new buyer demand back to the marketplace.

Challenges & lessons

Document a real challenge involving product matching, size-specific pricing, stale market data, or cross-channel inventory. Include what was learned and how the product response affected the seller experience.

What I’d change

A proposed next evaluation would follow a seller from initial listing to cross-channel sale, checking pricing clarity and inventory consistency. The next investment should follow observed friction; no experiment result is claimed here.