GET /v1/research/sold returns sellThroughPercent: the Nintendo Switch OLED search in our docs came out at 28.86% over the 3 years to October 10, 2026.The formula
Count the listings that sold in a period and the listings still active for the same search, then divide sold by the total. Use the same keyword, condition and marketplace for both counts, or the rate means nothing.
sell-through rate = sold listings / (sold listings + active listings) x 100
example: 120 sold and 280 still listed
120 / (120 + 280) x 100 = 30%By hand on eBay: search the item, note the number of results, then tick Sold items and note that number too. Since July 2026 eBay asks you to sign in before it shows sold results, and it only shows about the last 90 days.
What a good sell-through rate is
| STR | What it usually means |
|---|---|
| Above 50% | More sold than listed: demand beats supply, price to sell quickly |
| 20% to 50% | Healthy: worth stocking at the right price |
| Below 20% | Crowded: many listings, few buyers; expect to wait or cut price |
These bands are a common reseller rule of thumb, not an eBay rule. Expensive items (watches, cameras, graded cards) often sit well under 50% and are still very profitable, so read STR next to the median sold price and how recent the sales are. See why the median beats the average.
Get eBay's sell-through rate by API
GET /v1/research/sold returns a totals block on page 1 for the whole search and date range, including eBay's sellThroughPercent, units sold and the average sold price. It works for any window up to 3 years, on every plan including free. This is the example from our sold history docs:
from compsniper import CompSniper # pip install compsniper
client = CompSniper() # reads COMPSNIPER_API_KEY
# eBay's own sell-through for a keyword over any window up to 3 years:
data = client.history("nintendo switch oled", start_date="2023-10-11", end_date="2026-10-10", limit=10)
totals = data["totals"]
print(totals["sellThroughPercent"], totals["totalSold"], totals["averageSoldPrice"]["amount"])
# -> 28.86 491 382.74For a quick estimate of the last 90 days, compare the sold and active result counts of a normal search. Each call is one request:
def count(value):
return int("".join(ch for ch in str(value) if ch.isdigit()) or 0)
sold = client.sold("nintendo switch oled", count=1) # recent sold listings (about 90 days)
active = client.active("nintendo switch oled", count=1) # listed right now
s, a = count(sold["totalResults"]), count(active["totalResults"])
print(f"quick STR: {s / (s + a) * 100:.1f}%")To run this for a whole sheet of items, see eBay sold prices in Google Sheets.
Frequently asked questions
eBay sell-through rate
How do you calculate sell-through rate on eBay?
Divide the number of sold listings by the number of sold plus active listings for the same item, then multiply by 100. 120 sold and 280 still listed is 120 / 400 x 100 = 30%. With the CompSniper API, GET /v1/research/sold returns eBay's own sellThroughPercent for any window up to 3 years.
What is a good sell-through rate on eBay?
A common reseller rule of thumb: above 50% sells fast, 20% to 50% is healthy and worth stocking, and below about 20% means slow, crowded listings. Treat it as a guide, not a law: high-priced items often sell well below 50% and are still very profitable.
Does sell-through rate show how fast something sells?
Not on its own. STR shows demand relative to supply. Pair it with the dates of recent sales and the median sold price to see how fast and for how much an item sells.
Where can I see eBay sell-through rate without Terapeak?
CompSniper's GET /v1/research/sold returns eBay's sell-through percentage in its totals block for any keyword and date range up to 3 years, on every plan including free. You can also estimate it from the sold and active result counts of /v1/scrape.