Consumer Trust Barriers in the Used Goods Market

The used goods market is growing faster than first-hand retail, and online resale now makes up the dominant share of US resale spending. That growth has not translated into even participation. Cost consciousness has spread across income brackets rather than staying confined to budget shoppers, a shift McKinsey's State of the Consumer 2026 identifies as the "resourceful consumer" trend, and secondhand goods now have a broader addressable audience than at any point before. Yet a meaningful share of consumers still hesitate to buy used, or avoid it outright, even when price and selection favor doing so. A market this large should have resolved the hesitation by now through scale alone. It hasn't, and the gap between how big the market is and how big it could be is the question this piece sets out to answer.

Information asymmetry as the structural root of the problem

Consumers don't hesitate because they fail to understand secondhand goods or carry old stigma about buying used. It persists because sellers know more than buyers do about an item's condition, history, and authenticity, and nothing about market growth closes that gap on its own. New goods come with manufacturer warranties, standardized grading, and some kind of verifiable record. Secondhand items typically arrive with none of that. You can trust a new purchase without thinking twice, but that informational infrastructure simply doesn't exist by default in resale.

This isn't a problem caused only by dishonest sellers. Even a seller acting in good faith cannot fully communicate everything they know about an item's history, and a buyer has no way to verify a claim before money changes hands. Capgemini's What Matters to Today's Consumer 2026 finds that price alone no longer defines value for buyers: quality, trust, and emotional connection now shape purchasing decisions as much as cost does. That means buyers are walking into resale transactions with higher expectations right as the environment they're entering is least equipped to meet them. Product misrepresentation, information asymmetry, and seller opportunism all raise the rate of post-purchase trust violations recorded after purchase, and those violations drive buyers to abandon platforms. Market growth runs alongside this mechanism. It does not neutralize it.

Counterfeit goods and the sharpest point of buyer exposure

Counterfeiting is the most extreme expression of this asymmetry, because it strips away the one thing a buyer assumes they can take for granted: that the item is what the listing says it is. In several high-demand categories, counterfeit goods aren't just a marginal risk sitting at the edges of the market. They are the dominant outcome buyers run into. Apparel has become the highest-risk category: authentication data from one verification vendor shows that roughly a third of scanned apparel items could not be verified as genuine. That concentration of risk tracks the concentration of demand. Streetwear and luxury categories draw the heaviest counterfeiting activity precisely because that's where resale value is highest.

Exposure isn't distributed evenly across brands, either. Brands that keep tight control over their distribution channels see far lower counterfeit rates than brands with wide or loosely managed distribution. Part of this problem originates upstream, in supply-chain discipline, before an item ever reaches a resale platform. The newest layer of difficulty comes from "superfakes," counterfeits built from materials sourced from the same suppliers that make the originals. These fakes have deceived even professional brand authentication teams, so a buyer relying on personal judgment or a seller's word has no reliable way to catch what a trained authenticator missed.

The clearest recent demonstration of how far this problem reaches came from StockX. In March 2025, a federal judge ruled StockX liable for selling counterfeit Nike sneakers, and the case settled in August 2025. StockX built its brand identity around authentication, and the ruling showed that even a platform organized around verifying goods could not guarantee what it promised. The reputational cost of that outlasts the legal settlement. The RealReal's history of class-action litigation tells a similar story at the luxury end of the market: authenticators were reportedly given minimal training alongside strict processing quotas. Volume and verification rigor pull against each other, and when volume wins, the buyer absorbs the risk that rigor was supposed to catch.

Passing authentication does not resolve the buyer's exposure: condition misrepresentation as a second, distinct gap

Confirming that an item is genuine does not tell a buyer anything about whether it matches the condition the seller described. These are two separate claims, and platforms that treat them as one leave buyers with confidence they haven't actually earned. "Verified Authentic" means the item is genuine. "As described" means the item matches its listing. A platform can deliver the first without delivering the second.

StockX's long-standing no-returns policy shows how this plays out structurally. Once an item passed authentication, the sale was final. A buyer who received a sneaker that was genuine but in worse condition than advertised had no recourse. That policy stood until November 2024, when StockX introduced a voluntary 14-day return option because customers demanded it. The timing matters: StockX built in a buyer return option before the Nike counterfeit case had even settled. The original no-returns design was built for seller and platform certainty at the buyer's expense. That is exactly the outcome information asymmetry predicts when a platform doesn't correct for it.

The problem gets worse in peer-to-peer markets that don't hold the transaction themselves. Platforms that stay outside the transaction routinely send return requests back to the seller. A buyer's recourse depends on the goodwill of the very party that holds the informational advantage. And this isn't a rare outcome that only affects unlucky buyers. Most P2P platform users reported at least one problem in the past year, and most often it was poor quality of goods or services, or goods that didn't match their description. For a large share of people using these platforms, running into a problem is the typical experience, not an exception to it.

Review systems meant to compensate for information asymmetry reproduce the same problem

Peer reviews exist to give buyers a signal that sellers can't manufacture on their own, and on used goods platforms that signal is structurally tilted toward positive outcomes. The distortion doesn't come from satisfied buyers. It comes from incentives that suppress negative feedback regardless of what actually happened.

Only a minority of platform users check reviews regularly to begin with, and among users who experienced a real problem with a purchase, only a small fraction left a negative rating. That gap between how often problems occur and how often they get reported means the rating buyers see overstates how reliable a seller actually is. A buyer who depends on a seller's cooperation for shipping or dispute resolution has a practical reason not to burn that relationship with a bad review, and a seller has every reason to avoid retaliating against a buyer with a negative rating of their own. The two parties end up with aligned incentives to keep the public record clean, regardless of what the private experience was.

A high rating doesn't mean a seller had no problems; it means problems weren't reported, and those are two very different claims for a buyer to be relying on.

Who bears the cost of these barriers unevenly

These barriers don't land on every buyer equally. Information asymmetry works like a tax that falls hardest on exactly the buyers the resale market depends on most for its future growth, while buyers with more money and more options have the means to protect themselves from the worst outcomes.

Younger consumers, particularly Gen Z, buy secondhand more often than most, and a substantial share purchase secondhand apparel on a regular basis. They are the market's most active segment, and the trust failures described above land on them more often simply because they transact more often. At the same time, Gen Z trusts most of the channels people use to research products less than baby boomers do. So you get higher participation paired with lower baseline trust: the group most exposed to resale's trust failures is also the group with the least confidence going in and the weakest financial cushion for absorbing a bad transaction.

McKinsey's State of the Consumer 2026 identifies Gen Z as the cohort leading adoption of AI-driven shopping tools, and that could help close some of this gap. But an AI tool is only as useful as the data behind it, and in used goods that data is thin and largely unverified, so the tool can't offer much protection the underlying information doesn't support. Affluent buyers face a different set of options. They can absorb a loss if an authentication fails, pay for white-glove authentication services, or buy through brand-owned resale channels that carry built-in trust. The market's worst outcomes concentrate among the buyers least equipped to absorb them. If trust barriers disproportionately discourage the buyers who have the most to gain from secondhand's value proposition, the market keeps growing at the top while stalling exactly where its economic and environmental case is strongest.

Platform investment in closing the information gap and its commercial case

Platforms that have taken the information gap seriously have seen it pay off in measurable commercial terms. Trust infrastructure functions as a growth lever, not a cost to be minimized.

Bunjang, operating in South Korea, built a proprietary authentication system that combines visual inspection, scientific equipment, and AI trained on hundreds of thousands of data points. The platform reports very high authentication accuracy, and luxury goods now make up more than a quarter of its annual gross merchandise value, with both luxury transaction volume and value rising year-on-year through the first half of 2025. Both Carousell and Bunjang have said publicly that verification has helped their business grow. Those are self-reported claims, but they point in the same direction: cutting down information asymmetry drives more transaction volume, not just higher satisfaction scores among existing buyers.

The opposite case makes the same point from the other side. The RealReal's experience under volume pressure, where authentication rigor reportedly gave way to processing quotas, led to litigation, reputational damage, and buyers leaving the platform. Platforms that delay or deprioritize verification investment don't avoid the cost of information asymmetry. They defer it, and they tend to pay more for it later, in legal exposure and lost trust, than they would have paid by investing earlier.

The approaches now reducing information asymmetry, authentication technology, regulatory pressure, and brand-owned resale

Three distinct forces are currently compressing the information gap in used goods markets, and each works on a different layer of the problem: technology at the level of the individual item, regulation at the level of the platform, and brand participation at the level of the sales channel itself.

AI-driven authentication is the most visible of the three. Bunjang's system is built to keep adapting to new counterfeiting methods, which points to something important about how this technology has to work: effective authentication isn't a product a platform builds once and leaves alone. You maintain it continuously, as an ongoing technical commitment, as counterfeiters adjust their methods. But AI authentication has a clear limit. It confirms item identity far better than item condition: it solves counterfeiting but leaves misrepresented condition unaddressed. That second dimension needs a different set of tools: standardized condition grading, workable return policies, and buyer protections that don't depend on seller goodwill.

Regulatory pressure is building at the platform level, not the item level. The US INFORM Consumers Act now requires online marketplaces to collect, verify, and disclose information about high-volume third-party sellers, defined as those completing 200 or more sales totaling a minimum dollar threshold within a 12-month period, including bank accounts, tax IDs, and government IDs. This doesn't authenticate any individual product. It raises the accountability of repeat sellers directly, cutting into the anonymity that has made seller opportunism low-risk in the past. That makes it a structural complement to item-level authentication rather than a substitute for it: one tool verifies the item, the other makes the seller behind it harder to hide.

Brand-owned resale channels close the gap from a third direction entirely, by putting the party with the most complete information, the brand itself, directly into the transaction. A brand selling its own secondhand inventory doesn't need a third party to vouch for authenticity, because the brand is the original source of truth about the product. None of these three approaches solves the whole problem on its own. Together, they describe where the market's trust infrastructure is actually being rebuilt: item by item, platform by platform, and channel by channel.