Understanding peer influence in networks is critical to estimating product demand and diffusion, creating effective viral marketing, and designing ‘network interventions’ to promote positive social change. But several statistical challenges make it difficult to econometrically identify peer influence in networks. Though some recent studies use experiments to identify influence, they have not investigated the social or structural conditions under which influence is strongest. We investigate the two most prominent network characteristics that may moderate social influence between peers - tie strength and network embeddedness. By randomly manipulating messages sent by adopters of a Facebook application to their 1.3 Million peers, we were able to identify the moderating effect of tie strength and embeddedness on influence. We find that both embeddedness and tie strength increase influence. Individuals experience a 0.6% increase in influence over their peers for each friend they share in common with that peer. As the number of common friends can be quite large, this effect is also economically significant. Individuals exert 125% more influence on peers for each affiliation they share in common, 1355% more influence on peers with whom they attended the same college, and 622% more influence on peers that live in the same current town. However, the amount of physical interaction between friends, measured by co-appearance in photos, does not have an effect. This work presents some of the first large scale experimental evidence investigating the social and structural moderators of peer influence in networks. The results could enable more effective marketing strategies and public policy more broadly.