The Population Dynamics of Websites: [Extended Abstract]

Websites derive revenue by advertising or charging fees for services and so their profit depends on their user base -- the number of users visiting the website. But how should websites control their user base? This paper is the first to address and answer this question. It builds a model in which, starting from an initial user base, the website controls the growth of the population by choosing the intensity of referrals and targeted ads to potential users. A larger population provides more profit to the website, but building a larger population through referrals and targeted ads is costly; the optimal policy must therefore balance the marginal benefit of adding users against the marginal cost of referrals and targeted ads. The nature of the optimal policy depends on a number of factors. Most obvious is the initial user base; websites starting with a small initial population should offer many referrals and targeted ads at the beginning, but then decrease referrals and targeted ads over time. Less obvious factors are the type of website and the typical length of time users remain on the site: the optimal policy for a website that generates most of its revenue from a core group of users who remain on the site for a long time -- e.g., mobile and online gaming sites -- should be more aggressive and protective of its user base than that of a website whose revenue is more uniformly distributed across users who remain on the site only briefly. When arrivals and exits are stochastic, the optimal policy is more aggressive -- offering more referrals and targeted ads.