  An informed seller designs a dynamic mechanism to sell an experience good.
The seller has partial information about the product match, which affects the
buyer's private consumption experience. We characterize equilibrium mechanisms
of this dynamic informed principal problem. The belief gap between the informed
seller and the uninformed buyer, coupled with the buyer's learning, gives rise
to mechanisms that provide the skeptical buyer with limited access to the
product and an option to upgrade if the buyer is swayed by a good experience.
Depending on the seller's screening technology, this takes the form of
free/discounted trials or tiered pricing, which are prevalent in digital
markets. In contrast to static environments, having consumer data can reduce
sellers' revenue in equilibrium, as they fine-tune the dynamic design with
their data forecasting the buyer's learning process.
