Online platforms use customer reviews as a mechanism to help individuals utilize the "wisdom of crowds," overcome the hurdle of information overload, and choose the right product amongst countless options. However, with the exponential increase in online reviews, individuals now experience information overload with the number of available reviews. As a result, online platforms have introduced another form of crowdsourcing whereby readers vote on, and subsequently identify, helpful online reviews. While researchers have investigated what makes a review helpful (vs. not), researchers have widely ignored the downstream effects of helpful reviews. This research fills this gap by exploring how the helpfulness mechanism (the voting tallies of review helpfulness) impacts purchase outcomes. Using a fixed-effect model on a panel data of mobile applications, the authors find that after controlling for unobserved mobile app heterogeneity, helpfulness popularity (the average number of helpful votes) and helpfulness concentration (the skewness of the helpful votes distribution) impact app installation positively. Moreover, results show that helpfulness concentration magnifies the positive impact of helpfulness popularity. These results are consistent across endogeneity checks, several robustness tests, an alternative analysis to test the theoretical process, and an experiment. Finally, the authors provide several theoretical and managerial implications.