eBay Market Analyzer
Market intelligence for eBay resellers
Aggregates eBay sold listings to surface profitable categories, price trends, and sell-through rates. Layered with a Claude-powered agent that turns raw data into reseller-friendly briefings.
Open the live appproblem
eBay resellers spend hours per week sifting through completed listings to figure out what is actually selling, at what price, and how quickly — work that has to be redone every season.
solution
Flask service scrapes and normalises sold-listing data, computes category-level profitability metrics, and exposes a UI for filtering by margin, sell-through, and time-on-market. A Claude agent summarises trends in plain English.
architecture
external → compute → store → ui
outcome
Replaces hours of manual eBay browsing with a few minutes of dashboard reading. Surfaces profitable categories before they peak.
stack
capabilities
- →Sold-listing aggregation and deduplication
- →Price trend tracking per category
- →Sell-through and margin calculations
- →AI-generated category briefings
lessons learned
- 01Resilient scraping = polite rate limits + selector versioning. Site changes are not bugs, they are scheduled events.
- 02Profitability is a margin × velocity product. Optimising one without the other gives the wrong answer.
- 03AI summaries are most useful when they contradict the dashboard — they catch the categories I would have skipped.