Kahneman, Knetsch & Thaler 1990 showed Cornell students demanded roughly twice as much to sell a coffee mug as students without mugs would pay for one. The finding became the backbone of behavioral pricing. The 2005 Plott-Zeiler critique and List 2003/2004 market-experience studies showed the effect shrinks or disappears under specific conditions. A real laboratory phenomenon, stretched into a universal pricing law it cannot support.

Picture the SaaS pricing meeting. Someone has read Thinking, Fast and Slow over the weekend. The product team is debating whether to lengthen the free trial from fourteen days to thirty. A senior PM says, with conviction: “The longer the trial, the stronger the endowment effect. Users will feel like they own the product. They’ll value it more. They’ll convert at a higher rate.” Heads nod. The deck gets updated. The trial gets extended. Three months later, conversion is flat, churn is up, and nobody quite knows why the predicted lift didn’t materialize.

What just happened is the way the endowment effect lives in modern pricing discourse. It is invoked as if it were a universal law --- give someone an object, they value it more, charge them more --- and this universal-law version maps cleanly onto whatever pricing tactic the strategist is already inclined to pursue. Free trials. Money-back guarantees. Default upgrade plans. Pre-loaded credits. “Endowment” gets stretched to cover all of it.

The original research, by contrast, was much more specific. Daniel Kahneman, Jack Knetsch, and Richard Thaler ran a now-famous series of experiments in the late 1980s at Cornell. They handed undergraduate students coffee mugs and watched what happened when those students were asked to trade them. The students given mugs demanded substantially more to sell than the students without mugs were willing to pay. The findings were published in the Journal of Political Economy in 1990 and helped establish behavioral economics as a serious empirical project.

In the years since, the endowment effect has been simultaneously one of the most robustly demonstrated and most aggressively contested phenomena in behavioral economics. It does replicate, in many contexts. It also shrinks dramatically under specific procedural controls, and it largely disappears for experienced market participants trading commodities they’re familiar with. The honest summary is that the endowment effect is real, but it is more conditional than the pricing playbooks imply, and the boundary conditions are exactly where most “behavioral pricing” advice gets sloppy.

For CEOs and consultants evaluating behavioral-pricing claims, the question is not “is the endowment effect real?” but “is the specific tactic this person is selling me actually supported by what the endowment-effect research established, or are they smuggling in a much broader claim?” The smuggled-broader-claim version is what gets baked into product decisions and quietly underperforms.

What Kahneman, Knetsch & Thaler 1990 Actually Found

The canonical paper is Kahneman, D., Knetsch, J. L., & Thaler, R. H. (1990), “Experimental Tests of the Endowment Effect and the Coase Theorem,” Journal of Political Economy 98(6), 1325-1348 (DOI 10.1086/261737). It built on Jack Knetsch’s solo paper from the year before, Knetsch, J. L. (1989), “The Endowment Effect and Evidence of Nonreversible Indifference Curves,” American Economic Review 79(5), 1277-1284, which had used a chocolate-bar-versus-coffee-mug exchange experiment to make a related point.

The 1990 paper ran a series of related experiments. The most famous involved Cornell undergraduates and university-branded coffee mugs sold at the campus bookstore for around $6. In one set of trials, half the students in a session were randomly given a mug. The other half were not. Then a market was conducted: sellers (those with mugs) stated the minimum price at which they would sell, and buyers (those without) stated the maximum price they would pay. The experimenters then computed the market-clearing price and arranged the trades.

Standard microeconomic theory predicts that, because the mugs were assigned randomly, roughly half of the mugs should change hands. The students who liked mugs most should end up with them, regardless of who was initially given one. What actually happened was that very few trades occurred. The median asking price from sellers was roughly twice the median bid from buyers. Across the relevant trials, the median seller wanted around $5.25 to $7.00 to part with the mug, and the median buyer offered around $2.25 to $3.50. Trade volume was a small fraction of what would be predicted if students were valuing the mugs on their underlying preferences alone.

The authors ran additional variations to rule out alternative explanations. They tested whether the gap might be a “wealth effect” (sellers feel richer because they have a mug to sell, so they demand more) by adding a third group of “choosers” who were given the option of taking either the mug or a sum of cash. Choosers behaved more like buyers than sellers. They tested whether the gap might be the result of unfamiliarity with the market mechanism by repeating trials. The gap persisted. They tested whether it was specific to mugs by repeating with pens. The gap persisted.

The headline finding was clear and striking. People appeared to value an object they owned at roughly twice what they would pay to acquire the same object. The implications for the Coase theorem --- which holds that, absent transaction costs, the initial allocation of property rights does not affect the final allocation, because parties will trade until efficient --- were direct. The initial allocation appeared to matter quite a bit, because the act of being given an object seemed to change how it was valued.

For behavioral economics, this was foundational. The endowment effect became one of the most-cited demonstrations of the kind of reference-dependent valuation that prospect theory had predicted. It was treated as evidence that loss aversion operated even for trivial, low-stakes objects. It was used to justify a wide range of policy and pricing applications, from default rules in retirement savings to free trial periods in software.

The Plott & Zeiler 2005 Procedural Critique

In 2005, Charles Plott and Kathryn Zeiler published a challenge that has reshaped the literature in ways that most pricing books still haven’t caught up with. Plott, C. R., & Zeiler, K. (2005), “The Willingness to Pay-Willingness to Accept Gap, the ‘Endowment Effect,’ Subject Misconceptions, and Experimental Procedures for Eliciting Valuations,” American Economic Review 95(3), 530-545 (DOI 10.1257/0002828054201387), argued that the gap observed in the standard mug experiments was not necessarily evidence of an endowment effect at all. It might, they argued, be evidence of subject misconceptions about the experimental procedure.

Their reasoning is technical but the intuition is clean. The standard mug experiments used something called the Becker-DeGroot-Marschak procedure (or close variants) to elicit valuations. In this procedure, subjects state a price, then a market price is drawn at random; sellers must sell if the drawn price exceeds their stated price, buyers must buy if their stated price exceeds the drawn price. The mechanism is incentive-compatible: subjects’ best strategy is to truthfully state their actual valuation.

But the mechanism is incentive-compatible only if subjects understand it. Plott and Zeiler argued that, in the original Kahneman-Knetsch-Thaler experiments, subjects had limited training on the procedure, may have misunderstood the strategic structure, and may have engaged in strategic posturing rather than truthful valuation. Sellers, not fully understanding that overstating would cost them sales, might overstate to “leave room to negotiate.” Buyers, not fully understanding that understating would cost them purchases, might understate for the same reason. The observed gap would then reflect strategic confusion rather than a genuine asymmetry in preferences.

To test this, Plott and Zeiler re-ran the mug experiment with four key procedural changes. First, they used the Becker-DeGroot-Marschak mechanism with extensive training, including practice rounds with feedback. Second, they used an anonymous environment in which no subject’s behavior was observable to others. Third, they provided extensive verbal explanation of why truthful revelation was the subjects’ best strategy. Fourth, they used objects (mugs and pens) but with these procedural controls in place throughout.

Their result was striking. With the procedural controls, the WTA/WTP gap for mugs essentially disappeared. The median seller valuation and median buyer valuation were not significantly different. The gap that Kahneman, Knetsch, and Thaler had attributed to the endowment effect could, they argued, be substantially reproduced or eliminated by varying procedural controls.

A 2007 follow-up paper, Plott, C. R., & Zeiler, K. (2007), “Exchange Asymmetries Incorrectly Interpreted as Evidence of Endowment Effect Theory and Prospect Theory?” American Economic Review 97(4), 1449-1466, extended the argument to the exchange experiments (chocolate-bar-vs-mug) that had been a separate strand of the literature, finding similar procedural sensitivity.

The Plott-Zeiler critique did not go uncontested. Multiple subsequent papers have argued that, even with their procedural controls, real gaps exist in many contexts; a 2015 paper in European Economic Review reported a failed replication of Plott and Zeiler’s null result, finding the WTA/WTP gap persisted under their procedures. The field has not converged on a clean verdict. What is broadly accepted is that the magnitude of the gap is sensitive to procedural details in ways the early literature did not fully appreciate, and that “the gap shows up in some procedures and not others” is now a question rather than a settled answer.

For pricing strategists, the relevant point is not which side won the academic argument. The relevant point is that even sympathetic readings of the literature now acknowledge that the procedural setup matters a lot, and that real-world pricing situations are nothing like a Cornell laboratory anyway. The mapping from laboratory result to pricing tactic is not the clean one-to-one that pricing books treat it as.

List’s Market-Experience Studies

The other major source of moderation comes from a series of field studies by John List, an economist at the University of Chicago who specializes in running experiments outside the laboratory. List took the endowment effect to a real marketplace and asked whether it persisted in people who actually traded for a living.

The first paper was List, J. A. (2003), “Does Market Experience Eliminate Market Anomalies?” Quarterly Journal of Economics 118(1), 41-71. List ran endowment-effect experiments at sports-card and pin-trading conventions, where he could observe behavior from a population that ranged from novice attendees to highly experienced dealers who traded constantly. He used the same kind of elicitation procedures as the laboratory studies but in a realistic field setting with collectibles that the subjects actually cared about.

The finding was striking. Inexperienced traders --- people who attended their first or second convention --- showed the standard endowment effect. They were reluctant to trade an object they had been given for an object of equal nominal value, just as Cornell undergraduates had been. Experienced traders --- people who attended dozens of conventions a year and made trades constantly --- showed essentially no endowment effect. They were as willing to trade as standard economic theory would predict. The effect was strongly moderated by trading experience.

The 2004 follow-up paper, List, J. A. (2004), “Neoclassical Theory Versus Prospect Theory: Evidence from the Marketplace,” Econometrica 72(2), 615-625, used a larger sample (over 375 active marketplace participants) and a more rigorous design, and confirmed the basic pattern. The summary in the published paper is direct: “Prospect theory adequately organizes behavior among inexperienced consumers, but consumers with intense market experience behave largely in accordance with neoclassical predictions.”

List’s results matter for the pricing-strategy conversation in a specific way. They suggest the endowment effect is something like a default tendency that gets washed out by experience with the relevant market. People who don’t trade often are reluctant to give up what they have. People who trade often have learned --- presumably through some combination of explicit and implicit experience --- not to let that reluctance distort their decisions.

For B2B SaaS and consumer pricing, the population of users is often somewhere in between. Most users have some experience evaluating software products, but few are professional traders of subscription services. The relevant question becomes not “is there an endowment effect?” but “how experienced are my users in the specific domain where I’m asking them to make a valuation, and is that experience level enough to wash out whatever attachment they’ve developed?”

The 2014 Meta-Analysis Picture

The most thorough quantitative summary of the literature is Tunçel, T., & Hammitt, J. K. (2014), “A New Meta-Analysis on the WTP/WTA Disparity,” Journal of Environmental Economics and Management 68(1), 175-187 (DOI 10.1016/j.jeem.2014.06.001). Tunçel and Hammitt pulled together 76 studies that elicited both WTA and WTP measures of value for the same good, and analyzed the disparity as a function of study characteristics.

The headline number is that the average WTA/WTP ratio across all 76 studies was roughly 3.0 --- people demanded about three times as much to give up a good as they would pay to acquire it. This is, on its face, even larger than the canonical 2:1 ratio from the original Kahneman-Knetsch-Thaler experiments.

But the headline number is highly misleading on its own, because the heterogeneity across study contexts is enormous. The meta-analysis found that the WTA/WTP ratio was much larger for non-market goods (such as environmental goods like clean air or public-park access) than for ordinary private goods. For environmental and public goods, the ratio averaged over 6:1. For ordinary private goods (the closest analog to consumer products that businesses actually sell), the ratio was much smaller. For health-related goods and lottery tickets, the disparity was relatively small.

The meta-analysis also confirmed the procedural and experiential moderators that the literature had been arguing about. The disparity was smaller when subjects had real-market experience with the good. It was smaller when the elicitation procedure used incentive-compatible mechanisms with proper training. It was smaller for studies that used student subjects (interesting, given that the canonical mug study used students --- the meta-analysis suggests students may actually show somewhat smaller gaps than non-students, perhaps reflecting other procedural factors that correlate with using students). It was smaller for studies that used real (incentive-compatible) rather than hypothetical valuations.

For pricing strategists, the meta-analysis is the single most important data point in the literature. It says, clearly: the endowment effect is real (the average gap is large and statistically robust), but the size depends on the type of good, the subject’s experience, and the elicitation procedure. There is no universal multiplier you can apply to derive “what users will pay” from “what we should charge.”

When Endowment Effect Likely Applies

Taking the research seriously, here are the conditions under which the endowment effect is most likely to show up at substantial magnitude:

Non-market goods. Things people don’t routinely trade in markets --- environmental amenities, health states, irreplaceable personal possessions. The meta-analysis showed the largest gaps in this category.

Novice traders. People without much experience valuing the relevant good in market contexts. List’s research suggests this is the population that shows the laboratory effect at full strength.

Gift-status objects. Items that have been given to the person, especially as a gift or as compensation, and that have acquired emotional or identity significance. The original Cornell mug studies used objects given to the subjects for free; the gift framing may have contributed to the strength of the effect.

Irreversible ownership. Situations where the person cannot easily reverse the acquisition. The longer and more committed the ownership, the more the attachment is likely to form.

Unique or scarce items. Objects that cannot be easily replaced with substitutes. Fungibility erodes the endowment effect; uniqueness amplifies it.

Identity-linked goods. Things that have become part of how the person sees themselves --- a favorite mug at the office, a tool that defines a craft, a software setup that fits the user’s particular workflow. Identity-linked goods carry more endowment weight than commodity goods.

When It Likely Doesn’t

By contrast, here are conditions under which the endowment effect is likely to be small or absent:

Fungible commodities. Standard goods that are easily replaced. The original literature acknowledged that the endowment effect is largely absent for “money tokens” used in laboratory experiments and is small for commodity-like goods.

Experienced market participants. People who routinely buy and sell in the relevant market. List’s research is unambiguous on this.

Money itself. Cash and cash equivalents show essentially no endowment effect in the standard studies; this is why the original experiments used physical objects.

Reversible trial contexts. A “free trial” of a SaaS product is not the same kind of endowment as being given a physical mug at Cornell. The user knows the trial will end. The user knows the company is using the trial as a marketing tactic. The user has not been given the product as a gift; they have been given an explicit option to purchase. All of these conditions weaken the endowment-effect prediction substantially.

Sophisticated buyers. Procurement teams, professional buyers, anyone whose job involves evaluating products against alternatives. These populations have learned to discount their own initial attachment to a thing.

Tools without identity links. A backend monitoring tool that runs invisibly. A spreadsheet template that solves a one-off task. A utility that gets used and then forgotten. Low-identity-link goods carry minimal endowment weight.

What This Means For Pricing And Product Strategy

The single most common misuse of endowment-effect reasoning in pricing strategy is the assumption that any tactic that gives the user “possession” or “access” will trigger endowment effects and therefore raise willingness-to-pay. This logic gets applied to free trials, money-back guarantees, freemium tiers, default upgrade plans, pre-loaded credits, and a long list of related tactics. The implicit claim is that the laboratory effect translates cleanly into a pricing lever.

It probably doesn’t, at least not cleanly. Free trials do appear to increase conversion rates in many SaaS contexts, but the mechanism is more likely a mix of: commitment and consistency (users who have invested time learning a product are reluctant to switch), sunk cost (users who have invested setup work want to recoup the value of that investment), status-quo bias (users default to whatever they’re currently using), switching costs (the real cost of evaluating and migrating to an alternative), and only modestly endowment effects in the strict experimental sense.

The distinction matters because these mechanisms have different boundary conditions and different leverage points. If the conversion lift from a free trial comes mostly from switching costs and sunk costs, then the policy implication is to lower the friction of getting started inside the trial (so users invest more setup work) rather than to lengthen the trial (so they “feel like they own” the product longer). If it comes from status-quo bias, the implication is about making the post-trial state default to paid rather than canceled. The “endowment effect” framing tends to push toward longer trials and more “ownership” framing; the more accurate underlying-mechanism framing pushes toward different design choices.

For consultants and CEOs reviewing pricing proposals, the discipline is to ask: when someone invokes “the endowment effect” to justify a tactic, are they actually predicting that the WTA/WTP gap observed in laboratory mug experiments will reproduce in this specific user population, with this specific product, in this specific market context? Usually they are not. They are using “endowment effect” as a brand name for a broad class of attachment-related phenomena, and the specific empirical research underlying the brand name does not necessarily support the application.

The right experiment, in most pricing contexts, is to run an A/B test of the actual tactic against a control, measure the actual lift, and not pre-commit to a specific psychological mechanism for explaining the result. Often the result will be smaller than the endowment-effect framing would predict. Sometimes it will be larger, but for reasons other than endowment.

What This Means For Strategists Evaluating “Behavioral Pricing” Claims

The pattern recognition for evaluating pricing claims that invoke the endowment effect:

Invoking endowment effect for any pricing tactic that involves possession or access. The original research established a specific gap in a specific procedural context with specific kinds of objects. The casual transfer to “any tactic that involves giving the user something” is unjustified by the underlying research.

Ignoring market-experience moderators. Strategists who quote the endowment-effect literature without engaging with List’s market-experience studies are working with a literature that is at least two decades out of date. The fact that experienced traders show essentially no endowment effect is one of the most-replicated findings in the field, and it has direct implications for B2B contexts where the buyers are professionals.

Conflating endowment with related mechanisms. Commitment-and-consistency, sunk-cost reasoning, status-quo bias, switching costs, and loss aversion all produce attachment-like phenomena that look similar to the endowment effect but have different boundary conditions and respond to different design levers. Treating them all as “the endowment effect” loses the specificity that makes the underlying mechanisms useful to act on.

Quoting the 2:1 ratio (or 3:1, or whatever) as a planning parameter. No serious application of the endowment-effect research treats a specific WTA/WTP ratio as a number you can multiply willingness-to-pay by to derive a price. The ratios are sample statistics from very specific experimental contexts. They are not laws of human valuation that translate into product decisions.

Ignoring the procedural-critique literature. Anyone selling endowment-effect-based advice who has not engaged with the Plott-Zeiler critique is selling an older version of the literature than the field actually has now. The fact that procedural details matter to the magnitude of the laboratory effect is itself a warning that the laboratory result transfers messily to non-laboratory contexts.

The interesting tension here is that the endowment effect is, in some real sense, a vindication of the behavioral-economics project. The phenomenon does exist. The original researchers were not fabricating it. The basic finding has held up across many subsequent studies. This is not a “psychology in crisis” story in the same way that, say, ego depletion is. It is a more subtle story about a robust laboratory effect with clear boundary conditions getting stretched into a universal pricing-design law that the boundary conditions cannot support.

For the strategist, the takeaway is calibration. Take the endowment effect seriously as a real phenomenon. Take the boundary conditions equally seriously. Recognize that “endowment effect” in a pricing-strategy deck is often doing too much work, covering too many distinct mechanisms, applied to populations and contexts where the underlying research suggests modest effects at best. Run the experiment. Trust the data. Be honest about what the laboratory results actually established and what they did not.

Sources

  • Kahneman, D., Knetsch, J. L., & Thaler, R. H. (1990). Experimental tests of the endowment effect and the Coase theorem. Journal of Political Economy, 98(6), 1325-1348. DOI: 10.1086/261737
  • Knetsch, J. L. (1989). The endowment effect and evidence of nonreversible indifference curves. American Economic Review, 79(5), 1277-1284. URL: https://www.jstor.org/stable/1831454
  • Plott, C. R., & Zeiler, K. (2005). The willingness to pay-willingness to accept gap, the “endowment effect,” subject misconceptions, and experimental procedures for eliciting valuations. American Economic Review, 95(3), 530-545. DOI: 10.1257/0002828054201387
  • Plott, C. R., & Zeiler, K. (2007). Exchange asymmetries incorrectly interpreted as evidence of endowment effect theory and prospect theory? American Economic Review, 97(4), 1449-1466. DOI: 10.1257/aer.97.4.1449
  • List, J. A. (2003). Does market experience eliminate market anomalies? Quarterly Journal of Economics, 118(1), 41-71. DOI: 10.1162/00335530360535144
  • List, J. A. (2004). Neoclassical theory versus prospect theory: Evidence from the marketplace. Econometrica, 72(2), 615-625. DOI: 10.1111/j.1468-0262.2004.00502.x
  • Tunçel, T., & Hammitt, J. K. (2014). A new meta-analysis on the WTP/WTA disparity. Journal of Environmental Economics and Management, 68(1), 175-187. DOI: 10.1016/j.jeem.2014.06.001

FAQ

Should I use free trials?

Probably yes, but not because of the endowment effect. Free trials reliably increase conversion in many SaaS contexts; the underlying mechanisms are more likely a mix of commitment-consistency, sunk-cost reasoning, status-quo bias, and reduction in evaluation risk. The endowment-effect framing tends to push toward longer trials and more “ownership” framing; the more accurate underlying-mechanism framing pushes toward making it easy for users to invest setup work inside the trial, and toward default-to-paid post-trial structures. Test the specific tactic. Don’t assume a specific psychological mechanism.

What about money-back guarantees?

Money-back guarantees do appear to lift conversion in many contexts, and the endowment-effect logic is the most commonly invoked explanation (users who buy the product will be reluctant to return it because they now “own” it). The actual mechanism is plausibly a mix of: reducing perceived risk at point-of-purchase (the dominant effect), endowment-style attachment post-purchase (real but smaller than the marketing-textbook claim), inertia and hassle costs of actually initiating a return, and status-quo bias. Refund rates in most categories are much lower than the share of buyers who would say at point-of-sale that they “might” return. That’s evidence of something --- but the something is not specifically the laboratory endowment effect, and the implication for whether to offer the guarantee is independent of which mechanism explains it.

What about pricing decoys?

Different mechanism, different literature. The decoy effect (also called asymmetric dominance) is about how the presence of a third, dominated option shifts choice between two non-dominated options. It is not the endowment effect. The two are sometimes treated as part of the same “behavioral pricing” toolkit, but they have different empirical bases and different reliability profiles. The decoy effect has its own replication issues that are worth understanding separately.

Is the endowment effect real or not?

Real, yes. The phenomenon has been demonstrated in many studies across many contexts. What is contested is the magnitude, the boundary conditions, and whether the standard laboratory procedure measures the construct it’s claimed to measure. The honest summary is that the effect is real but moderated by experience, procedural design, type of good, and probably other factors that the literature has not yet fully mapped. “Real but conditional” is the right framing. “Universal pricing law” is not.

Does the endowment effect work in B2B SaaS?

Probably less than in consumer contexts, because B2B buyers tend to have more market experience with software products and are buying on behalf of organizations that have purchasing processes designed to mute individual psychological effects. Procurement teams in particular are likely to show essentially no endowment effect in the strict sense, because evaluating-and-replacing is literally what they do for a living. Where endowment-like effects do show up in B2B, they are usually about embedded workflow and integration (which raises switching costs) rather than about attachment to the product itself.

What about pre-loaded credits or “free” usage tiers?

These can produce real conversion lifts, and the endowment-effect framing is one common explanation. The more rigorous explanation in most cases involves a combination of: reducing the user’s risk at the start (no commitment required), creating opportunities for the user to invest setup work and develop habits, and providing a clear comparison point (“you used X credits this month, here’s what additional credits would cost”). Whether the lift comes specifically from endowment-style attachment is hard to isolate from these other factors. The design implication is to make the setup-work-investment side of the equation strong, not just the “free credit” side.

Did Kahneman and Thaler retract or modify their endowment-effect work?

No. Both authors continued to defend the basic finding throughout their subsequent careers. Thaler in particular has written extensively about the endowment effect in his more popular work (including Misbehaving, 2015). The serious scholarly contestation has come from other researchers --- primarily Plott and Zeiler on the procedural side, and List on the market-experience side. Kahneman and the other authors have generally responded by emphasizing that the laboratory effect remains robust in many contexts and that the boundary conditions matter without invalidating the core finding. This is a fair characterization of where the literature now sits.

What’s the single most important thing to remember when someone invokes the endowment effect in a pricing meeting?

Ask them what specific empirical prediction they are making, in your specific user population, with your specific product, and what experiment would test it. If they cannot answer in those terms, they are using “endowment effect” as a vibes-based brand name rather than as an empirical hypothesis. The brand-name version is not what the underlying research supports. The hypothesis version --- “we predict a specific lift of X% from this tactic, attributable to endowment-style attachment among inexperienced users in our specific context, testable via a specific A/B test design” --- is what the research can actually back, and is what should drive the pricing decision.

replication-crisis endowment-effect behavioral-economics pricing-strategy evidence-evaluation
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Atticus Li

Experimentation and growth leader. CXL-certified CRO practitioner, Mindworx-certified behavioral economist (1 of ~1,000 worldwide). 200+ A/B tests across energy, SaaS, fintech, e-commerce, and marketplace verticals.

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