艾媒咨询 | 2025年中国在线音频市场消费行为调查数据

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随着音频内容生态的持续升级，在线音频用户行为呈现多维特征，主要覆盖以通勤时段知识学习、睡前放松场景为例的碎片化应用领域，以有声书沉浸体验、播客社交互动为例的内容消费领域，以及智能硬件互联、AI语音交互为代表的技术融合领域。根据全球新经济产业第三方数据挖掘和分析机构iiMedia Research（艾媒咨询）最新发布的《2025年中国在线音频市场消费行为调查数据》数据显示，喜马拉雅以45.52%的市场份额占据行业领先地位，头部效应显著。用户接触在线音频平台的主要渠道集中于内容分享平台（小红书、知乎等），占比达42.98%，内容丰富度则成为选择平台的核心考量。在用户行为层面，放松心情为用户的主导需求，有声书与脱口秀类节目以超32%的喜爱度并列内容偏好榜首。原创性与时效性被用户视为音频内容的核心竞争力。知识付费产品选择中，音质音色、内容丰富度及界面设计构成决策关键三角。艾媒咨询分析师认为，平台需强化内容生态建设，通过AI技术优化个性化推荐，提升创作者扶持力度以激发优质内容产出，同时深化智能硬件联动与场景适配，构建“内容+技术+场景”的全链条服务体系，方能持续激活用户价值。
With the continuous upgrading of audio content ecology, online audio user behavior presents multi-dimensional characteristics, mainly covering the fragmented application fields such as commuting knowledge learning and bedtime relaxation scenes, the content consumption fields such as audio book immersion experience and podcast social interaction, and the technology integration fields represented by intelligent hardware interconnection and AI voice interaction. According to the latest "Consumer behavior survey data of China's online audio market in 2025" released by iiMedia Research, a third-party data mining and analysis institution in the global new economy industry, Himalaya occupies the industry leader position with a market share of 45.52%, and the head effect is significant. The main channels for users to contact online audio platforms are concentrated in content sharing platforms (XiaoHongshu, Zhihu, etc.), accounting for 42.98%, and content richness has become the core consideration in choosing platforms. In terms of user behavior, relaxing mood is the dominant demand of users, and audiobooks and talk shows rank the top of the content preferences list with over 32% of the likes. Originality and timeliness are regarded by users as the core competitiveness of audio content. In the selection of paid knowledge products, sound quality, sound color, content richness and interface design constitute the key decision triangle.iiMedia Research believe that the platform needs to strengthen the content ecological construction, optimize personalized recommendation through AI technology, enhance creator support to stimulate quality content output, and deepen intelligent hardware linkage and scene adaptation, build a "content + technology + scene" full chain service system, in order to continue to activate user value.