What this Marketplace Comparison calculator tells you
Run one item scenario through ten fee models and sort the estimated results by net payout.
The headline output is a ranked table rather than a single rate: one item scenario pushed through ten fee engines and sorted by estimated net payout. It answers which channels are worth researching, not which one to list on.
How the Marketplace Comparison calculator works
The comparison uses a representative default category and US seller assumptions for each platform. It is a screening tool, not proof that an item is eligible, desirable, or equally likely to sell on every marketplace.
Money is converted to integer cents before any fee is calculated. Percentage charges round at the fee boundary, and totals are assembled from those already-rounded lines. That mirrors how a transaction statement reads and avoids the floating-point drift that produces an unexplained penny.
What the ten fee models do and do not include
Category, seller country, taxes, payment path, advertising, subscriptions, shipping programs, returns, audience, and time to sale can outweigh the displayed fee difference.
The percentage marketplaces
Several of the ten charge a straightforward percentage of the sale with no threshold and little structure. These are the easiest to compare and the easiest to model, and for a mid-priced item they usually cluster within a few points of each other.
Where they differ is the base. Some apply the percentage to the item price alone and others include buyer-paid shipping and sometimes tax, which means two platforms with the same headline rate can take materially different amounts from the same order.
For heavy items this base difference frequently outweighs the rate difference. A platform charging a lower percentage on a wider base can easily cost more than a higher percentage on the item alone, which is exactly the comparison a headline table would get wrong.
The tiered and capped models
Some platforms change rate at a threshold or stop charging past a cap. Those structures make the effective rate price-dependent, so a comparison run at one price point can invert at another — and the ranking on this page is only valid for the scenario you entered.
Caps favour high-value goods and thresholds usually penalize the price band immediately above them. If your inventory sits near either boundary, the comparison deserves to be run at two or three prices rather than one.
This is the strongest argument against memorizing a league table. The order of these ten platforms genuinely changes with price, and a seller who learned the ranking on a fifty-dollar item will apply it wrongly to a five-hundred-dollar one.
Fixed per-order charges
Fixed amounts are what separate the platforms at the cheap end. A per-order charge that is irrelevant at two hundred dollars can be the largest single deduction at ten, and it is the reason the ranking of these ten is different for low-value inventory.
Run the comparison at the price you actually sell at. A model built at a comfortable mid-range price will rank the platforms in an order that simply does not hold where most of your volume sits.
Where a platform uses a flat fee below a threshold rather than a percentage, the effect is more extreme still, and cheap inventory can be structurally unattractive there regardless of how favourable the platform looks at higher prices.
What this comparison deliberately does not model
The comparison uses a representative default category and United States seller assumptions for each platform. It does not model subscriptions, promotional rates, high-volume programmes, seller status, or account-specific arrangements, all of which can move the real number.
It also does not model eligibility. Several of these marketplaces are category-specific — gear, records, streetwear, handmade — and an item that computes well against a platform it cannot legitimately be sold on has not told you anything useful.
Nor does it model advertising, which on some platforms is optional and on others is effectively unavoidable above a size threshold. Where advertising is mandatory in practice, the modeled rate understates the real one for any seller of consequence.
Realized price is the variable that decides it
Holding price constant across ten platforms is what makes the comparison arithmetically clean, and it is also the assumption most likely to be wrong. The same item does not fetch the same price everywhere, and the differences are frequently larger than the entire fee spread.
A platform taking four points more but realizing twenty percent higher prices is not the expensive option — it is the profitable one. Fee comparison answers a narrow question and this is the wider one it cannot see.
Use the table to build a shortlist, then rerun it with channel-specific prices drawn from actual sold listings. That second pass is where the comparison stops being a curiosity and starts being a decision.
Time to sale, workload, and dispute risk
Cash velocity belongs in the comparison. An item that sells in a week at a slightly lower payout may be worth more to the business than one that sells in six months at a better rate, because the capital comes back and buys the next item.
Operational workload differs sharply between these platforms. Live selling, negotiation-heavy marketplaces, and communities that expect detailed condition documentation all consume seller time that a fee model treats as free.
Dispute and return profiles differ too. A platform with a favourable fee schedule and a high return rate in your category can be the more expensive place to sell once the returns are counted, and none of that appears in a rate comparison.
Subscriptions, status tiers, and volume programmes
Several of the marketplaces on this table offer a paid subscription or a performance tier that changes the rate. A store plan, a preferred-seller status, or a volume programme can move the effective percentage enough to reorder the comparison entirely.
The catch is that the benefit is a function of your volume on that specific channel, not of the rate. A plan that pays for itself at four hundred listings is a straight loss at forty, so the same subscription genuinely improves and worsens the same seller depending on where the inventory sits.
This comparison models standard published rates without subscriptions, so it is the right baseline and the wrong final answer for anyone paying for a plan. Recalculate your shortlist with your own adjusted rate before treating the ranking as settled.
Cross-listing, duplicate sales, and operational load
Listing the same item on several marketplaces raises the chance of a sale and introduces the risk of selling it twice. A duplicate sale means a cancellation, and cancellations cost account standing on every marketplace in this table.
The operational cost is also real. Every additional channel adds photography conventions, category mappings, message threads, and returns policies, and that overhead scales with channels rather than with sales.
None of it appears in a fee comparison. A seller choosing between two marketplaces whose rates differ by two points is usually making a decision dominated by workload and realised price, and the fee table is the smallest of the three inputs.
Payout timing across the ten
The marketplaces here settle very differently. Some pay out on a fixed schedule, some on request, some deduct fees at the point of sale and some invoice them later, and holds on new accounts are common across all of them.
For a seller reinvesting into inventory, settlement speed can matter more than a percentage point of commission. Two channels with identical effective rates are not equivalent if one funds next week's sourcing and the other funds it next month.
This table compares what a sale earns, not when it pays. Treat settlement as a separate column you fill in from your own experience of each channel — it is not published consistently enough to model here.
Category rules, restrictions, and what each channel will actually accept
Fees are only relevant on marketplaces that will list the item at all. Category restrictions, brand gating, authentication requirements, and outright prohibitions remove channels from the comparison before the rate matters.
Some of those constraints are soft. A marketplace may technically accept a category while having almost no buyer demand in it, which is functionally the same as a prohibition and considerably harder to notice.
Condition rules differ too. What counts as acceptable used condition, what must be disclosed, and how returns are adjudicated all vary, and they vary in ways that change your realised cost rather than your fee.
Shipping expectations are the third constraint. Channels with aggressive delivery promises push you toward faster services, and that cost lands on you regardless of what the commission table says.
Run this comparison across the channels that would genuinely accept and sell your item. A ranking that includes a marketplace where the item cannot list is arithmetic without a decision attached.
Auditing your own effective rate against this table
The rates here are published ones. Your actual effective rate is computable from your own records: total fees charged over a period divided by total sales over the same period, per channel.
That figure is almost always higher than the published percentage, because it contains promotions you opted into, fixed charges spread across small orders, and the occasional dispute or adjustment. The gap between the two is the most useful number in this whole exercise.
Run it per channel and per price band rather than as one blended figure. A single number across all your sales averages away exactly the structure — thresholds, caps, fixed amounts — that this comparison exists to expose.
Then come back and re-run the comparison with your own rates in place of the published ones. The ranking that produces is the one worth acting on, and it will not necessarily match the one this page shows by default.
What one item nets on each of the ten marketplaces
Holding price, shipping, and basis constant is what makes the ten results comparable, and it is also the assumption most likely to be wrong, since the same item rarely realizes the same price everywhere. Read the spread, then rerun the shortlist with channel-specific prices.
| Item price | Total fees | Net payout | Effective rate |
|---|---|---|---|
| $10.00 | $0.60 | $9.40 | 6.0% |
| $50.00 | $2.10 | $47.90 | 4.2% |
| $100.00 | $3.75 | $96.25 | 3.8% |
| $500.00 | $16.95 | $483.05 | 3.4% |
Which marketplace takes the least from a sale?
For a given scenario the table above will name one, but the honest answer is that the smallest fee rarely decides the outcome. Category eligibility, audience, realized price, time to sale, return risk, and the labor each channel demands routinely outweigh the gap. Treat the winner as the first place to look, not the place to list.
The ranking this page produces is valid for the scenario you entered and no other. Thresholds, caps, and fixed charges mean the order genuinely changes with price, so a comparison run once at a comfortable price point will mislead you about the inventory that makes up most of your volume.
And the fee gap is usually the smaller variable. Realized price differences between marketplaces routinely exceed the entire spread of fees on this table, which is why the shortlist matters more than the winner and why the second pass with channel-specific prices is the one that decides anything.
Using a fee gap without letting it pick the channel
Treat the highest payout as a research prompt rather than a decision. The comparison has told you where to look; confirming category eligibility and current rates is what tells you whether the option is real.
Rerun the shortlist with channel-specific prices taken from actual sold listings. Realized price differences between marketplaces routinely exceed the entire fee spread, which makes the second pass more decisive than the first.
Then compare the things the fee model cannot see: demand depth, buyer trust, operational time, return risk, and how quickly capital comes back. A cheaper platform that sells slowly is often the more expensive choice.
Where cross-listing is practical, treat the fee difference as a tiebreaker rather than a strategy. The gain from being visible in two markets usually dwarfs the gain from choosing the marginally cheaper one.
Shortlist on realised price first and fees second. The price gap between channels routinely exceeds the entire fee spread on this table, which makes fees a tiebreaker rather than a decision.
Test a channel with a small, representative batch rather than a full catalogue. The published rate is knowable in advance; realised price, time to sale, and dispute rate are not, and only the batch tells you.
Revisit the comparison when your average order value shifts. Thresholds and fixed charges mean the ranking that was right for twenty-dollar inventory can be wrong for eighty-dollar inventory on the same schedules.
Consolidate onto fewer channels than you think you need. Each additional marketplace adds category mapping, message volume, and duplicate-sale risk, and the marginal channel is often the one that quietly consumes the operating margin the others earned.
Negotiate nothing and audit everything. Published rates are not negotiable for individual sellers, but the gap between the published rate and your realised rate is entirely within your control, and it is usually larger than the spread between any two platforms on this table.
Channel-specific pricing and target margin
Cross-listing decisions should optimize expected contribution, not fees alone. Expected contribution combines the payout with the probability and speed of a sale, and a lower-fee marketplace can easily produce a worse expected outcome on all three.
Price per channel rather than uniformly. Each of these marketplaces has its own price expectations, its own audience, and its own fee structure, and a single price copied across all of them will be too high in some and leaving money behind in others.
Set a floor that holds everywhere and a target that varies by channel. The floor protects you from accepting a bad sale on whichever platform moves first; the channel-specific target is what captures the difference between a market that values the item and one that merely tolerates it.
Price per channel rather than uniformly. The same item can support a materially different price on two marketplaces, and copying one price across all of them leaves money on the table on at least one.
Where a channel supports a higher price, take it rather than copying a single price everywhere. Uniform pricing across marketplaces is convenient and it systematically underprices on the strongest channel.
Build a comparable fee base across ten marketplaces
The mechanic that decides every other number on this page is that the comparison projects shared price, shipping, basis, fulfillment, and advertising inputs into each platform’s representative US fee engine. That one sentence tells you which amount belongs in each field. A percentage means nothing until its base is fixed, and marketplaces do not treat item price, buyer-paid shipping, handling, and tax the same way. Where the actual receipt uses a broader base than the model, the receipt wins and the model is what needs correcting.
The discontinuity worth knowing is that representative categories keep the comparison legible, but caps, thresholds, Store rates, and specialist programs require the dedicated calculator. Test values immediately below, exactly at, and immediately above a threshold whenever a sale lands near one, and do not average the two sides together — the marketplace applies its published formula, and an average conceals the exact dollar difference this page exists to surface. Fixed charges create the mirror-image problem, because their effective rate climbs as the order shrinks.
This page assumes a reseller screening one item across nine marketplaces before researching channel eligibility, audience fit, and likely realized price. Start from one concrete transaction rather than a blended monthly rate: name the item, the price you expect to realize, the buyer-paid shipping, the inventory basis, the label you will buy, the packing supplies, and the seller program. Anything still unknown should stay visible as an assumption instead of being folded into a percentage where nobody can audit it.
Set a channel-specific expected price before you shortlist
The offer rule here is that the same item rarely realizes the same offer everywhere, so rerun the shortlist with platform-specific expected prices before choosing a winner. Enter the price a buyer is likely to actually pay rather than the public list price, then update any seller-funded shipping, promotion, or service that transaction would trigger. Goal-seek mode reverses the question: give it the profit you need and it searches for the minimum item price in whole cents, running the same engine so tiers, caps, and fixed charges stay inside the answer.
On fulfillment, one shared shipping assumption makes fee output comparable, but real platform labels, buyer expectations, package programs, and local options can differ. Keep the buyer charge and the purchased label as two separate lines. Netting them early hides whether shipping contributes, breaks even, or quietly consumes the item margin, and it corrupts the fee base wherever a marketplace charges on the buyer-paid amount. Weigh and measure the packed parcel rather than the bare item; dimensional weight makes light, bulky boxes cost more than the scale suggests.
The decision worth writing down before you touch an input is which channel deserves deeper research after fees, expected sale price, sell-through, workload, trust, returns, and cash velocity are considered together. Without a stated decision it is easy to optimize the most visible fee line while ignoring realized price, conversion, handling time, or return exposure. Save three scenarios — expected, conservative, and downside — and set the floor from the conservative one, because a floor built on the expected case breaks the first time an unmodeled charge appears.
Reconcile a screening estimate against the platform receipt
The minimum evidence set for this channel is platform-specific order histories, expected and actual price, fees, labels, returns, listing time, labor, basis, and days held. Keep it at order level even where the marketplace only summarizes monthly activity: order-level records are what make a fee discrepancy traceable, and they let category, campaign, shipping, and return patterns be compared without guesswork.
Before relying on a result, open the dedicated platform page, select the actual category and program, verify current rates, model the likely price, and compare operational evidence. Work the reconciliation in order — buyer-paid total, then every fee and credit, then the payout movement — and connect cost basis and fulfillment separately. The arithmetic should explain the gap between gross revenue, net payout, contribution profit, and cash actually received. Timing differences belong in a note, not forced into the wrong order.
The exceptions this model does not try to predict include category eligibility, seller country, tax bases, subscriptions, payment programs, advertising, label programs, returns, audience, and time to sale. They are named rather than silently averaged in, because false precision is worse than a stated unknown. Decide which belong in the immediate scenario and which should be carried as a reserve built from your own completed-order history. When an actual charge differs, classify the variance before changing any checked-in schedule; an account-specific line stays an exception.
Turn one comparison into a cross-listing rule
On channel choice, the highlighted payout is a screening result rather than a recommendation; the best channel maximizes expected contribution under realistic demand. A fee difference is a research prompt, not a verdict — it says nothing about eligibility, demand, buyer trust, or the probability that the item sells at all. Build a channel-specific expected price from sold evidence, adjust for condition and buyer total, estimate days to sale, and only then compare expected contribution.
An estimate earns its keep when it changes what you source, list, promote, or accept. Tag this Marketplace Comparison scenario with a repeatable cohort — category, price band, source, condition, package class, expected days to sale — and review enough completed orders to tell a durable rule from one lucky result. State the rule in terms you can check from stored order evidence, or it will quietly drift back into intuition.
Revise the rule when the published schedule, the seller program, your packaging method, the category mix, or buyer behavior moves, and keep the effective date so older orders stay explainable. The Marketplace Comparison rates on this page carry their own reviewer and review date; your sourcing and operating costs are private business facts and need a review owner of their own.
Frequently asked questions
Which marketplace has the lowest selling fees?
There is no single answer, because the ranking changes with the price and with whether you charge shipping. Percentage-only marketplaces win on cheap items where a fixed per-order charge would dominate; marketplaces that cap or taper their commission win on expensive ones; and the ones that charge their commission on buyer-paid shipping move down the list as soon as shipping is not free. Enter your price and shipping above and the table ranks all ten for that specific sale.
How accurate is this ten-marketplace comparison?
Each row runs that platform’s checked-in, cited schedule in integer cents, so the arithmetic is exact. The comparison is still a screen: it assumes a representative category and a US seller for every channel, and real eligibility varies.
Does Instica collect the numbers I enter?
No. The calculation runs entirely in your browser. The financial figures you type are not transmitted to or stored by Instica.
What revenue figure should the comparison start from?
One realistic buyer-paid total, held constant so the ten fee engines stay comparable. Once you have a shortlist, rerun each channel with the price you actually expect to realize there.
Why do the effective rates differ so much between platforms?
Because the fee bases differ, not only the percentages. Some charge on buyer-paid shipping, some only on item price, some add a fixed per-order amount, and thresholds and caps arrive at different points.
Does the top result mean I should list there?
No. It means that channel is worth researching. Confirm category eligibility and current rates, then weigh demand, buyer trust, operational time, return risk, and cash velocity before committing.
What if one of the ten schedules is past its review date?
The build fails once any schedule passes its next-review date, and a page already deployed shows a browser-side caution. Until it has been reviewed, treat that platform’s row as provisional and confirm from the cited source.
Do all ten platforms charge fees on shipping?
No, and that difference is a large part of the spread you see. Some apply a selling fee to buyer-paid shipping, some apply only payment processing to the order total. Open a dedicated calculator to see which applies.
Are buyer taxes included in this estimate?
Only the fields shown are modeled. Some marketplaces include buyer-paid tax in a processing or final-value-fee base, and tax varies by destination and order. If this Marketplace Comparison calculator shows no buyer-tax field, compare the estimate against the actual order statement before booking it.
Does the comparison include advertising?
Only if you enter a rate, and it then applies the same rate everywhere. Real ad economics differ by channel, so treat any promoted scenario here as a rough screen and verify it on the dedicated page.
Where do cost basis and packing supplies belong?
Cost basis is what the inventory item cost you. The purchased label goes in actual shipping cost, and mailers, boxes, tape, insurance, and cleaning go in the nearest visible cost field. Keep labor and overhead in a separate operating view so this Marketplace Comparison scenario stays a per-order contribution figure.
Should I compare list prices or accepted offers?
Accepted offers, channel by channel. Negotiation norms differ enough between these marketplaces that a single list price across all ten will rank them wrongly.
How often are the ten schedules checked?
Each has a named reviewer, a verification date, an archived copy of the official source, and a staggered next-review date, so they do not all expire at once. A weekly watchdog re-checks the source evidence.
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