In online auction marketplaces, item misrepresentation is one of the most common forms of seller deception. The impact of coarse-grained incentive manipulations on deceptive seller behavior in online markets had not been studied. We demonstrate experimental control over seller honesty, quantify this behavior relative to ground truth, and link it to personality. We recruited 62 experienced online auction sellers to handle seven jewelry items (some flawed) and generate auction advertisements. Independent variables included demographics, personality, and an incentive manipulation: maximize returns, avoid negative reputation, or a Control condition. Dependent variables involved the inclusion or exclusion of honest information. Reputation incentives led to significantly more reported flaws (30%) than other conditions (17%), all ‘hiding’ flaws in the middle of descriptions. More experience in selling items significantly predicted honesty, while extraversion and neuroticism predicted dishonesty. Design features can reduce seller deception and enhance buyer detection of deception: reputation systems should be highly salient to sellers, while buyers should consider images over text, and descriptions could be shuffled to expose honest information.