Explainability is crucial for building trust in traditional recommendation systems, yet its role in conversational settings is underexplored. Across three experimental studies (N = 1,429), we used between-subjects designs featuring diverse product categories (cameras, smartwatches, headphones) to examine the interactive effects of post hoc explanations (expert validation-based vs. consensus validation-based) and decision-making domains (hedonic vs. utilitarian) on consumer responses to conversational recommendations. We further examined how consumer decision-making styles (intuitive vs. rational) and user interfaces (text-based vs. voice-based) moderated these effects. Results show that post hoc explanations enhance perceived transparency and interpretability, thereby increasing consumer trust in conversational recommendations. In text-based interfaces, consumers making hedonic decisions preferred consensus-based explanations, whereas no clear preference emerged for utilitarian decision-makers. In voice-based interfaces, utilitarian consumers favored consensus-based explanations, while no significant preference was observed for hedonic decisions. Furthermore, intuitive consumers preferred consensus-based explanations for hedonic decisions and expert-based explanations for utilitarian decisions. Rational consumers consistently favored consensus-based explanations across both decision-making domains. These findings provide valuable insights for designing conversational recommendation systems on e-commerce platforms. By tailoring explanations to decision domains, user interfaces, and consumer decision-making styles, businesses can foster greater trust and engagement, driving more favorable purchasing behaviors and improving business outcomes.