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Jan28
Where Noisy Data Meets Standards (The Noisy Data arc, Part 9)
NextStage: Predictive Intelligence, Persuasion Engineering, Interactive Analytics and Behavioral Metrics Now in part 9 of the The Noisy Data Arc we continue our discussion of technological plateaus. This entry deals with how business both defines and recognizes plateaus.

Defining plateaus is great for business, branding and consumer mindshare. When you want a softdrink and automatically ask for a Coke, you're demonstrating a standard which had defined a plateau. This is true when you want a tissue and ask for a Kleenex, make a copy and say you've Xeroxed something, ... In each case the plateau is defined.

 

The point where an existing plateau ends in a shift to a new plateau is -- in the terms of tools and tool users co-evolving -- where business and economics recognize a disruptive technology occurs. Disruptive technologies are disruptive because they redefine the plateau, give rise to another plateau, create an intersecting plateau which forces the market to shift in response, ...

I know you'll be shocked (Shocked, I tell you!) to learn that when I first formed a company around the technology ("Evolution Technology" or "ET") based on my research I was told it was a disruptive technology. Fortunately I knew nothing about economics and even less about business so I usually responded with "Okay."

Why was ET disruptive? Because ET didn't care about clickthroughs or Time-On-Site or EntryPage or ExitPage. ET cared about "The reason I'm typing isn't the reason you're typing", ie, "I'm typing at my keyboard right now but the fact that I'm typing right now is the act expressing the internal state (psychological behavior). When you type at your keyboard are you expressing the same internal state that I am right now?"

The reason ET cares about these things is because ET's origins aren't in web analytics or the internet in general. It's not on the plateau of the web at all nor does it trace its family tree through the evolution of web analytics tools since the early 1990s. People reading Reading Virtual Minds know it grew out of a completely different set of paradigms.

Where ET meets the web is in its ability to deal with "One of the challenges I've always had with analytics is that they deal with what's happening at the machine, the computer, and not in the heart and mind of the person sitting at the computer" because the data ET routinely works with is what traditional web analytics defines as "noisy". Understanding cognitive, motivational/effective and behavioral elements has always been, to me, much more interesting than "How long was somebody on a page?", "What page did someone enter a site on?", "What page did someone exit a site at?" and so on.

The downside of coming from a completely different paradigm and dealing with what most people consider noisy data is that (in NextStage's case) the tools (ET) are either stoneknives or cellphones to most people investigating them.

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