To wit:

“[0087] If a document is returned for a certain query and over time, or within a given time window, users spend either more or less time on average on the document given the same or similar query, then this may be used as an indication that the document is fresh or stale, respectively. For example, assume that the query “Riverview swimming schedule” returns a document with the title “Riverview Swimming Schedule.”

“Assume further that users used to spend 30 seconds accessing it, but now every user that selects the document only spends a few seconds accessing it. Search engine 125 may use this information to determine that the document is stale (i.e., contains an outdated swimming schedule) and score the document accordingly.”

Good article. Just to be very careful with what I have said, I have not seen proof either way that bounces are factored into SE algorithms yet, although I suspect they are in a small way already. However, I am quite certain that as the clock ticks, they will increasingly be part of the algorithms.

I read Adam Lasnik’s quote to be contradictory to that of Matt Cutts. Matt seems to be trying to steer us away from thinking about bounces, without actually saying they don’t factor them in. Adam seems to be trying to steer us toward thinking about bounces, without actually saying they do factor them in.

Cryptic? You bet!