eBay market research, three years deep

90 days is a snapshot, not a study

The public sold page and most sold data APIs stop at 90 days, which hides every curve that matters: seasonality needs a full year, depreciation needs two or three, and a launch cliff only reads against the months before it. CompsAPI pages through up to 1,095 days of completed sales for any keyword, so the chart is real rows, not interpolation.

curl -G https://api.compsapi.com/v1/sold \
  -H "Authorization: Bearer YOUR_KEY" \
  --data-urlencode "q=iphone 14 pro" \
  --data-urlencode "days=1095" \
  --data-urlencode "best_offer=1"

Depreciation, measured

Our homepage chart is live API output: iPhone 14 Pro average sold price, down 30 percent across 24 months. The same query shape answers trade in curves, buyback schedules, insurance values and residual pricing for any product that trades on eBay, which is most products.

Volume is half the signal

Every response carries the rows, not just a price, so monthly sales counts come free: demand cliffs after a successor launches, category growth, format mix between auctions and fixed price, and the share of sales that closed as accepted Best Offers with best_offer=1. Count rows per month, group by format, and the dataset is a market report.

Clean inputs for models

Condition filters split new from used markets, minus words remove accessories and parts, and time based paging returns no duplicates between pages, so a 1,095 day pull lands analysis ready. Each row carries price, last_sold to the minute, format and shipping_cost for landed price series.

Start free

100 requests a month free covers a few full three year studies. Email keys@compsapi.com for a key, and see the API reference for paging details.