Passive conversation discovery, guided by the algorithms of Google and Bing and their analysis of vast amounts of social media data, may be the way we discover what conversations are happening that may be of interest. Much like Amazon’s book recommendation systems which looks at “people like us” and sees what they are interested in, Google and Bing may soon be able to accurately detect and show specific conversations that are most likely to be of interest to each person. We're pleased to present a guest post by Steven Woods , CTO of Eloqua and author of Digital Body Language, who shares his thoughts on where communication is headed -- and how marketers can prepare. Over time, the way in which communication happens has gone through some very interesting transitions.

Conversion rates, for example, the rate at which clicks convert to leads (and a key metric for B2B campaigns), can be improved significantly by reducing the number of irrelevant clicks. Negative keywords work like filters that prevent ads from showing when queries include keywords that you deem to be irrelevant, and they’re one of the most under-utilized tools for reducing wasteful PPC spending – dollars spent on clicks that don’t convert into qualified leads. Success in paid search (PPC) is often defined as generating quality clicks and conversions at the lowest possible cost.

Let's take a look at a possible scenario: David, a prospect, enters a search term into Google and finds an article your company wrote about why it's critical to solve a problem he's facing. David clicks on the link and reads the article where he discovers the information he needs to persuade Joe in product development that he can actually get something he's been wanting for a long time, but didn't know could be solved as part of the deal. David hunts Joe down, shares the insight and the article. Joe calls Susie and discusses the implications with her. Think