We consider the problem of deriving optimal advertising policies for the spread of innovations in a social network. We seek to compute policies that account for i) endogenous network influences, ii) the presence of competitive firms, that also wish to influence the network, and iii) possible uncertainties in the network model. Contrary to prior work in optimal advertising, which also accounts for network influences, we assume a dynamic model of preferences and we compute optimal policies for either finite or infinite horizons. We also compute robust optimal policies in the case where the evolution of preferences is also affected by external disturbances. Finally, in the presence of a competitive firm, we compute optimal Stackelberg and Nash solutions.