Paper detail

The user base dynamics of websites

In this work we study for the first time the interaction between marketing and network effects. We build a model in which the online firm starts with an initial user base and controls the growth of the user base by choosing the intensity of advertisements and referrals to potential users. A large user base provides more profits to the online firm, but building a large user base through advertisements and referrals is costly; therefore, the optimal policy must balance the marginal benefits of adding users against the marginal costs of sending advertisements and referrals. Our work offers three main insights: (1) The optimal policy prescribes that a new online firm should offer many advertisements and referrals initially, but then it should decrease advertisements and referrals over time. (2) If the network effects decrease, then the change in the optimal policy depends heavily on two factors i) the level of patience of the online firm, where patient online firms are oriented towards long term profits and impatient online firms are oriented towards short term profits and, ii) the size of the user base. If the online firm is very patient (impatient) and if the network effects decrease, then the optimal policy prescribes it to be more (less) aggressive in posting advertisements and referrals at low user base levels and less (more) aggressive in posting advertisements and referrals at high user base levels. (3) The change in the optimal policy when network effects decrease also depends heavily on the heterogeneity in the user base, as measured in terms of the revenue generated by each user. An online firm that generates most of its revenue from a core group of users should be more aggressive and protective of its user base than a firm that generates revenue uniformly from its users.

preprint2015arXivOpen access

Signal facts

What is known right now

Open access3 authors1 topic

Next steps

Decide what to do with this paper

Use like or dislike for the fast social read. The more specific scholarly feedback stays available below when needed.

Log in to curate

Reading frame

Keep the important context close to the paper

Keep the important signals around this paper in one place: votes, save state, collection context, reviews and the metadata you need before deciding what to do next.

Institutions

Add specific reaction

Move through the context

Research map

Open full explorer

Move through nearby people, institutions, topics and adjacent work without leaving the paper page.

Building this map preview

BZPEER is loading the nearby papers, people, topics and institutions for this page.

Structured reviews

0 review(s)

ContributeLeave structured feedbackUse the review template when you have a concrete strength, concern or method question.Open review form

No structured reviews yet. High-signal critique starts here.

Work discussion

0 comment(s)

DiscussAdd a high-signal commentKeep quick notes, caveats and replication pointers separate from formal reviews.Open comment form

No discussion yet. The first strong comment sets the tone.