Recent high-profile failures of domestic robotic products suggest more research is needed on factors that impact consumers’ willingness to purchase robots, and the success rates of the consumer robotics industry compared with other innovative technologies. Using data from two crowdfunding sites (Kickstarter and Indiegogo), we summarize the applications, forms, prices, contexts of use, target populations, and sociality of potential consumer and home robots. We then use statistical analysis, predictive modeling, and word co-occurrence to determine which characteristics are associated with increased product support by early market consumers, finding that health and fitness, security and monitoring, and general education applications, cartoon-like and animal-like robot forms, and single user group robots have significantly more backers. We also find that social robots have a mean of 1.2–3.2 times as many backers as non-social robots and that every twofold increase in price results in a 20% decrease in financial supporters. Product reviews from these sites are additionally used to identify product features consumers found important. Finally, analyses of the failure rates of social and home robots find that these products are not failing more frequently than other innovative products overall. This research is among the first to study factors influencing consumers’ purchasing behavior of home robots, and to use data mining methods to gain insights into home and consumer robot design.

近期国内机器人产品备受瞩目的失败表明，需要对影响消费者购买机器人意愿的因素以及与其他创新技术相比消费者机器人产业的成功率进行更多研究。我们使用来自两个众筹网站（Kickstarter和Indiegogo）的数据，总结了应用程序，形式，价格，使用环境，目标人群以及潜在消费者和家用机器人的社交性。然后，我们使用统计分析，预测模型和单词共现来确定哪些特征与早期市场消费者增加产品支持相关，从而发现健康和健身，安全和监控以及通识教育应用（卡通和动物）例如漫游器表单，并且单用户组漫游器具有更多的支持者。我们还发现，社交机器人的支持者平均数量是非社交机器人的1.2-3.2倍，价格每提高两倍，财务支持者的数量就会减少20％。来自这些站点的产品评论还用于识别消费者认为重要的产品功能。最后，对社交和家用机器人的故障率进行分析后发现，与其他创新产品相比，这些产品的故障率没有更高。这项研究是第一个研究影响消费者购买家用机器人行为的因素，并使用数据挖掘方法来深入了解家用和消费者机器人设计的研究之一。来自这些站点的产品评论还用于识别消费者认为重要的产品功能。最后，对社交和家用机器人的故障率进行分析后发现，与其他创新产品相比，这些产品的故障率没有更高。这项研究是第一个研究影响消费者购买家用机器人行为的因素，并使用数据挖掘方法来深入了解家用和消费者机器人设计的研究之一。来自这些站点的产品评论还用于识别消费者认为重要的产品功能。最后，对社交和家用机器人的故障率进行分析后发现，与其他创新产品相比，这些产品的故障率没有更高。这项研究是第一个研究影响消费者购买家用机器人行为的因素，并使用数据挖掘方法来深入了解家用和消费者机器人设计的研究之一。