Pricing in Social Networks under Limited Information

We model the choices of a monopolist who faces a partially uninformed population of consumers. She aims at expanding demand by exploiting his (limited) knowledge about consumers’ social network. She offers rewards to current clients in order to induce them to activate their social network and to convince peers to buy the product sold by the company. The program is profitable provided that the monopolist faces a serious enough informational problem and that the cost of investment in the social network is not prohibitively high. Price for informed consumers is lowered by the introduction of the reward compared to the benchmark where no program is run. There are no effects on the price charged to uninformed consumers. The offer of bonuses affects individual incentives of informed people to share information, determining a minimal degree condition for the costly investment in the social network. The level of such threshold strongly depends on the distribution of connections in the social network. In random networks, roughly the most popular half of informed consumers invests, regardless of network density. On the contrary, in scale-free networks the monopolist faces a clear-cut decision between maximising margins (running a small referral program) and maximising demand (motivating many informed agents to communicate). The optimal choice depends on the probability of observing highly-connected individuals. In empirically observed scale-free networks, the first alternative would be preferred, in line with real-world markets.