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We consider pricing in settings where a consumer discovers his value for agood only as he uses it, and the value evolves with each use. We explore simpleand natural pricing strategies for a seller in this setting, under theassumption that the seller knows the distribution from which the consumer'sinitial value is drawn, as well as the stochastic process that governs theevolution of the value with each use.  We consider the differences between up-front or "buy-it-now" pricing (BIN),and "pay-per-play" (PPP) pricing, where the consumer is charged per use. Ourresults show that PPP pricing can be a very effective mechanism for pricediscrimination, and thereby can increase seller revenue. But it can also beadvantageous to the buyers, as a way of mitigating risk. Indeed, thismitigation of risk can yield a larger pool of buyers. We also show that thepractice of offering free trials is largely beneficial.  We consider two different stochastic processes for how the buyer's valueevolves: In the first, the key random variable is how long the consumer remainsinterested in the product. In the second process, the consumer's value evolvesaccording to a random walk or Brownian motion with reflection at 1, andabsorption at 0.

How to sell an app: pay-per-play or buy-it-now?