Why Sellers Underestimate What Their Used Items Are Worth

A particular country's recommerce market is huge, growing several times faster than traditional retail, and yet most people selling into it are leaving money on the table. OfferUp's 2025 Recommerce Report found that 54% of American adults sold a secondhand item in the past year. That's a mainstream activity now, with tens of millions of transactions behind it. That's tens of millions of transactions, and a whole lot of them close at the wrong price.

Everyone talks about the buyer side of this boom: the savings, the sustainability angle, the inflation relief of not buying new. Fair enough. But nobody talks about what sellers actually walk away with, and the honest answer is: usually less than the item was worth. A bigger market doesn't fix that; it just means the underpricing scales right along with everything else. It just means the underpricing scales right along with everything else. More sellers, more transactions, more money quietly left on the table.

To understand why, you have to start before the listing even goes up. Before the photo, before the price field, before any of it. You have to start inside the seller's head.

Two opposite ways the endowment effect misleads sellers

The endowment effect usually gets described one way: people overvalue things simply because they own them. You've heard this. It's why your uncle won't sell his baseball cards for what they're actually worth, and why garage sale haggling always ends with someone saying "but it's a family piece."

Less discussed is the mirror image, and it's just as costly. When a seller is emotionally done with an item, ready to clear it out, detached from it, the bias flips. "I just want this gone" becomes its own price anchor, and it anchors low. Both versions come from the exact same root problem: the price is being set by a feeling, not a fact.

Picture the seller pricing a childhood toy at five bucks because it's clutter taking up shelf space, no different in their mind from an old phone charger. Meanwhile nostalgia-driven demand has quietly pushed that toy's real value to forty dollars. Same bias. Opposite direction. The toy doesn't know it's supposed to be cheap, it just is, because the person selling it feels like it should be.

A study out of the Journal of Business Research (Chua and Liao, 2010) found that online resale behavior gets shaped by psychological reference points that have nothing to do with actual market prices. Which tracks. Feelings are not spreadsheets, and pricing by feeling is a coin flip at best.

Bias is one problem. The other is structural, and arguably worse: sellers don't have access to the right data, and the data they do see is actively working against them.

Why active listings are the wrong data source

Open the app, search your item, look at what other people are asking, price yourself a little under that. Open the app, search your item, look at what other people are asking, price yourself a little under that. Feels smart. Feels like research. It is, in fact, a trap.

Active listings show asking prices. Active listings show asking prices, and that's all they show. That's all they show. They represent what sellers hope to get, and a huge chunk of those listings will sit there for months and never sell at that number. Pricing off active listings is like deciding what your house is worth by looking at a neighbor's place that's been sitting on the market, unsold, for three years. The price on the sign means nothing if nobody's paying it.

Facebook Marketplace makes this worse by design, or at least by omission: it doesn't surface sold prices the way eBay does. So on the single biggest local-selling platform in the country, pricing without cross-checking eBay's sold comps is basically guessing with extra steps.

Adding it up, sellers anchor to an inflated number (other people's wishful asking prices) and then price below that inflated number, which sounds cautious but produces a price that's neither grounded in real demand nor actually competitive. It's the worst of both directions at once.

Meanwhile, buyers who bother to check sold prices before making an offer know more about the item's value than the person selling it. That's a significant edge. That's the whole negotiation, decided before it starts.

What quality uncertainty does to prices in secondhand markets

Asking a seller to rate the condition of their own couch makes them freeze. Is it "good"? "Very good"? Does the scratch on the armrest matter? Does it matter that the remote for the massage feature went missing two years ago? Yes, that's a thing now.

Nobody trains people to grade their own stuff, so when sellers are uncertain, they default to shading the price down. It's a hedge. They treat their own uncertainty about the item as if it were a risk the buyer needs to be compensated for, even when the item is in genuinely great shape. The buyer gets a discount they never asked for and didn't earn. The seller just handed it over out of nerves.

This is the quiet cost of not having an objective condition grade. A shared, objective condition standard gives both sides a common reference point. Once there's a shared standard, the seller can price with confidence instead of pricing defensively.

Accessories play into this more than people expect. Original chargers, remotes, manuals, the box it came in: including those items can lift the achievable price meaningfully. But only if the seller thinks to list them, and understands that a complete set reads as higher quality than "here's the thing, minus everything that came with it."

How sold comps work, and what adjustments matter most

The rule is simple, even if it's underused: price off completed, paid transactions. On eBay, the "sold" or "completed" filter shows what identical items actually sold for, not what some other seller hoped for and never got. That filter is the closest thing most categories have to ground truth. eBay Terapeak extends that further with historical sell-through data, for anyone who wants to see trends rather than a single snapshot.

Condition matching is where sloppy comps fall apart. A worn item shouldn't be compared to a mint one. Don't compare an incomplete set to a full one. Don't compare untested electronics to something the seller confirmed powers on. Each shortcut there is a specific, quantifiable pricing mistake, not a rounding error.

A Closo story tells of a seller who found a rare Herman Miller chair component at a flea market, guessed it was worth around $150, listed it, and sold it in four minutes flat. Later found out it was worth closer to $600. Four minutes isn't a triumph. Four minutes is a siren. Speed of sale is a signal, and a fast sale almost always means the price was too low, not that the seller made a great call. An immediate sale is rarely a sign of good pricing.

Repricing deserves a routine, not a one-time guess: list at the target price, drop it if there's no bite after a couple of weeks, take another look a month out. Repricing also refreshes the listing itself, which can affect how many potential buyers encounter it.

Categories where sellers most reliably underprice

Some categories are almost designed to fool the person selling them.

Vintage gaming hardware sits at the top of the list. NES, SNES, Genesis, Game Boy: nostalgia-driven demand is strong and only getting stronger, and a rare Nintendo 64 or PlayStation title can go for hundreds, sometimes thousands. A seller who doesn't check first treats these as "old toys," which is exactly the mistake the buyer is counting on.

Electronics with demand nobody saw coming are their own category. Early-2000s point-and-shoot cameras have seen renewed demand that most original owners never anticipated. Someone who bought one of these in 2006 almost certainly has no idea it's cool again.

Then there's the unglamorous stuff. TV remotes, routers, calculators sound like junk drawer filler, but replacement-parts data from ZIK Analytics shows over 1,200 of these parts sold in a single 30-day window, worth more than $24,000 combined, at roughly a 13% sell-through rate and an average price near $8. Low per item, steady in volume, and almost entirely ignored by casual sellers who assume nobody wants a used remote. Somebody wants the remote.

Power tools hold value better than most people assume: DeWalt, Makita, Milwaukee all carry brand premiums that a seller who sees "used drill" instead of "Milwaukee M18" is going to miss completely.

Home goods follow a similar pattern. Bread makers, juicers, air fryers used twice and shoved in a cabinet, complete kitchenware sets, these get discounted because they feel ordinary to the person selling them. Buyers, meanwhile, are pricing against what it costs to buy new, which is a much friendlier comparison than the seller realizes.

Luxury goods are their own multibillion-dollar resale segment. Louis Vuitton, Chanel, Gucci: buyers treat these as investments. A seller who sees an "old bag" and prices it like an old bag is giving away appreciation that already happened.

And high-end baby gear, UPPAbaby strollers, Montessori-style toys, gets undersold constantly by parents who feel a little guilty about what they paid retail and just want it gone fast. Meanwhile there's a whole buyer base actively hunting for exactly this stuff, sustainability-minded and willing to pay well for it.

Choosing where to sell

Knowing an item is worth more doesn't matter if it's listed somewhere nobody's looking, or if the fees quietly eat the upside.

eBay reaches an enormous, mostly global buyer pool, which makes it the strongest option for electronics, tools, collectibles, anything with demand beyond a twenty-mile radius. Standard fees run around 13 to 14% combined on common categories, which needs to be baked into the price, not discovered afterward.

Facebook Marketplace, as of 2026, charges nothing for local sales. That's a real gap on mid-range items: a $75 item sold locally nets $75, versus a noticeably smaller number on the same sale through eBay once fees come out. Facebook Marketplace also supports nationwide shipping now. As of February 24, 2025, prepaid shipping labels were no longer provided by the marketplace platform for new listings, though the platform brought back prepaid labels for sellers between August and September 2025. Whichever version is live, that shipping cost has to get folded into the price, or the "no fee" advantage evaporates on the shipping line.

eBay listings also show up inside Facebook Marketplace at no extra cost to the seller, so listing once can reach both audiences without double the work.

Category fit still matters on top of all that. Furniture and anything bulky moves faster locally through Facebook Marketplace, nobody wants to ship a couch. Collectibles, vintage gaming, and niche electronics do better reaching eBay's deeper, more specific buyer pool. Fashion tends to find its crowd on Poshmark and Depop. Trading cards and collectibles have real momentum on Whatnot's live-sale format.

None of this is separate from pricing. It is pricing. Setting a number without accounting for the platform's fee structure means the item was underpriced before the listing even went live.

Why most sellers never fix their pricing, and what removes the barrier

None of this is a mystery once it's laid out. So why doesn't it happen?

Because the research burden stacks up fast across sold comps, condition adjustments, fees, platform choice, and listing copy. Look up sold comps. Adjust for condition. Calculate the fees. Pick the right platform for the category. Write a listing that actually communicates condition instead of just saying "good condition, some wear." Each step alone is manageable. All of them together is enough friction that most people just price by gut, or don't bother listing the item.

That gap appears in the numbers on pricing versus participation. OfferUp's 2025 Recommerce Report puts more than half of Americans in the "sold something secondhand" camp, but participation isn't the same as pricing it well. Most sellers are not running sold-comp research before they hit "list."

People will put in the work, but only for the item they already suspect is valuable. That leaves a long tail of smaller stuff, the remotes, the kitchen gadgets, the old cameras, permanently underpriced or never listed at all, because it didn't feel worth the research effort for a low-value item. Multiplying that by however many households have a junk drawer means the number stops being small.

The fix isn't convincing people to love spreadsheets. Nobody's doing that, and nobody should have to. The fix is shrinking the number of steps between "I own this thing" and "it's listed at a price backed by something real."

AI-powered listing tools that identify an item from a photo, grade its condition, and pull real sold-comp data to set a price go after all three problems at the same time. The pricing stops coming from a feeling and starts coming from data, which kills the endowment effect at the root. The sold-comp research that a seller would otherwise skip gets done automatically. And the condition grading happens without requiring the seller to become an expert in their own couch.

Snap a photo, get the item identified, get a condition grade, get a listing built off real market data instead of a guess. That's the shortcut. Not because sellers are lazy; they're not. The friction was always real, and the information gap was always structural. Close both, and the pricing gap closes with them, without anyone needing to become a professional reseller first.

Every closet, garage, and junk drawer with a "maybe I'll sell this someday" pile has something in it worth more than its owner thinks. The only real question is whether that gets discovered before the box gets driven to a donation bin for free.