Cascade, a first-of-its-kind tool analyses of the structures which underlie sharing activity on the web
Will Salkeld posted the above video to his blog a couple of weeks ago. it's a demonstration of a new kind of tool, called Cascade, which allows for precise analysis of the structures which underlie sharing activity on the web. it links browsing behavior on a site to sharing activity, thereby constructing a detailed picture of how information propagates through the social media space...
whilst questioning the practical value of the tool, describing Cascade as an "unnecessary complication to an already muddled social media landscape", Salkeld does observe that the tool could have specific and tangible benefits:
"tools like this could cut out much of the guess work that occurs when trying to determine who appropriate influencers should be. Knowing which people will propagate information or subvert it to their liking in advance will mean improved economies of scale, because the most appropriate influencers will already be apparent. The beauty of it is that as data accumulates, assumptions become more accurate!"
quite right too. but the ambition for a generation of tools like Cascade shouldn't be limited to the Twittersphere or even digital realms. the opportunity, and The Grail for media connections planning and measurement, is an all-media equivalent of Cascade; a tool that measure and allows interpretation of how communications spread through networks and populations.
this is of value to brands and marketers, who have obvious interest in understanding which communications lead to (sales) effects in market. but its also of huge interest to agencies. when you're paid by results, as bonus and increasingly base fees are, knowing - and proving - which impacts contributed to the sale becomes valuable information indeed.
in online its called attribution modelling. how do you attribute the value of the end sale to the various and constituent media impacts that let to it. 100% of attribution shouldn't go to the last impact (often Google) - this is just the last in a series of impacts that contributed to, and deserve 'credit' for part of the sale.
as planners, the idea that we could model attribution across multiple impacts and channels is intriguing at the least. and as media becomes digitised, the ability to track the impacts becomes tantalisingly feasible. as the pursuit of planning Grail's go, attribution modelling across channels is more than worth some time with a shrubbery or two.
