Content selection based on consumer interactions

A computer-implemented method for selecting content to be presented to a consumer, wherein content is selected from a content library stored on at least one storage medium, the content library being stored as a collection of sets of content, each first set of content comprising one or more pieces of content and being related to at least one other set with an indication of a likelihood that the consumer will want to consume content of the first set close in time to content of the other set, the method comprising acts of:

• (A) presenting a first content from a first set to the consumer;
• (B) if the consumer consumes the first content in entirety, selecting a second content from the first set to present to the consumer next;
• and
• (C) if the consumer skips the first content, selecting content from a second set, wherein the second set is related to the first set by the likelihood, and the second set is selected to have a likelihood inversely proportional to a number of recent skips of the consumer.

At least one computer-readable storage medium having stored thereon a data structure, the data structure storing a content library as a collection of records, the data structure comprising:

• at least one record defining a first set of content, each record comprising:
• at least one subrecord identifying a piece of content that is in the first set, and
• an identification of at least one other set stored in another record, and an indication of a likelihood that a consumer will want to consume content of the first set close in time to content of the at least one other set,
• wherein the data structure enables performance of a method of:
• selecting content for presentation to the consumer from a second set having a low likelihood that the consumer will want to consume the first set close in time with the second set, if it is determined that the consumer is skipping a number of content pieces within the first set that exceeds an established threshold.