Sell-through odds

Chance an item sells in 30, 60 or 90 days.

Convert a monthly sell chance into the odds an item has sold by day 30, 60 or 90. It is base-rate arithmetic on a number you enter, framed as modelling, not a prediction about any item.

If each month an item has probability p of selling, independently, the chance it has sold within n months is 1 − (1 − p)ⁿ. At p = 30% that is 30% after one month, 51% after two and 65.7% after three. The 30% is an example; use your own.

1 − (1 − p)ⁿExpected sales from a batchOptional monthly fadeAverage and median wait

Worked example

Suppose you believe an item has a 30% chance of selling in any given month. The chance it has not sold after one month is 70%; after two, 0.7 × 0.7 = 49%; after three, 0.7³ = 34.3%. So the chance it has sold within 30, 60 and 90 days is 30%, 51% and 65.7%. Of 20 identical listings, the model expects about 6, 10.2 and 13.1 to have sold by those dates. The average wait is 1 ÷ 0.3 = 3.33 months and the median wait is ln(0.5) ÷ ln(0.7) = 1.94 months, so averages run longer than medians because a few items sit a long time.

How the model works

Methodology. This is the geometric distribution: the first month in which a sale happens. With a constant monthly probability p, P(sold within n months) = 1 − (1 − p)ⁿ, the expected wait is 1/p months, the median is ln(0.5) ÷ ln(1 − p), and the months to a 90% chance is ln(0.1) ÷ ln(1 − p). The optional fade lowers the chance each month by a percentage you choose, because listings usually get stale; with a fade the closed forms for averages are not shown. Expected sold of a batch = listings × probability. The chance at least one of a batch has sold uses the same independence assumption.

Where does p come from? Your own history: the sell-through rate calculator turns counts into a rate, and the days of inventory tool turns that into time. Then use the result in the hold or markdown and income models, and see capital turnover for what slow sales do to your money.

Limits you should keep in mind

Items are not identical coins: a $12 shirt and a $300 camera have different p, and p depends on price, photos, season and demand. A single monthly p cannot capture that, which is why the page asks you to enter it and offers a fade rather than claiming a probability. Treat the output as a way to compare your own assumptions, for example whether 30% a month and 12 months of waiting is consistent with your goals, not as the odds that a given item will sell.

How to use it well

To estimate your own monthly chance, take items listed in a month and count how many sold within the following thirty days, then divide. Do it for each price band or category separately, because a single blended number hides big differences. Enter the result here, add a fade if older listings clearly sell less, and read the 60 and 90 day lines against your holding costs. If the chance of selling within 90 days is lower than you would accept for the money tied up, that is a signal to price differently or to use the hold or markdown calculator on those items.

What this tool does not cover

Any real probability that a particular item sells. The monthly chance is your input.
Dependence between items, seasonality, price changes and listing quality, apart from the optional fade.
Platform search ranking or listing-duration rules.
Money. For profit and holding costs use the hold or markdown and income calculators.
Tax treatment. General information only.

Sources (retrieved October 2026)

Shopify inventory reports: one published definition of sell-through rate (sold / (sold + still in inventory)). Retrieved October 2026.
eBay fee tables: final value fee percentage and per-order fee used as the default inputs. Retrieved October 2026. Rates differ by category and change, so check the page for your category.

Every other number on this page is an input you type or an assumption labelled as an example. Results vary, and nothing here is an income claim.

FAQ

What is the chance an item sells within 90 days?

With a constant monthly chance p, it is 1 − (1 − p)³. At 30% a month that is 65.7%; at 10% it is 27.1%. Your own p decides it.

Is this a prediction?

No. It is a model: if the chance each month is what you entered, these are the consequences. It cannot know whether that chance is right for your item.

What is a good monthly sell chance?

There is no universal figure. Measure your own sell-through and use it, then test how sensitive your plan is to a lower number.

What does the fade do?

It reduces the chance each month by the percentage you enter, to reflect listings going stale. With 0% you get the plain geometric model.

What if the chance is 0% or 100%?

At 0% nothing ever sells in the model. At 100% every item sells in the first month.

Estimate only

These pages are arithmetic on the numbers you enter. They do not predict what you will earn, and results vary widely with sourcing skill, category, season, platform rules and luck. This is not a promise of income. Fee defaults were read from eBay’s own pages in October 2026 and change. Not tax, legal or financial advice; see the IRS pages cited for your tax position.