This study investigates how iBuyers—firms offering instant home purchases based on algorithmic pricing—face significant challenges due to adverse selection. Drawing on a rich dataset of transactions and listings, I show how unobserved house quality interacts with private impatience value, often resulting in lower-than-expected returns for iBuyers. Using a model that disentangles private impatience value from unobserved quality I propose a redesigned revenue-sharing contract. By offering a lower upfront payment and sharing a portion of resale revenue, iBuyers can attract sellers with houses of higher unobserved quality, thereby mitigating adverse selection. I show how different contract parameters—such as the share of resale revenue—can enhance profitability. These findings underscore the broader lesson that markets relying heavily on algorithmic pricing must carefully account for private information to avoid unintended selection effects.