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The Hype Cycle: Social Reaction to Adopting New Technology

 

Gartner’s hype cycles are well known to market researchers in the technology industry, but the framework is valuable for other researchers as well when studying emerging product categories.

Here’s the basic curve:

Gartner hype cycle

And here’s how Gartner describes it:

It's a familiar story—A new innovation gets introduced to great fanfare [Technology Trigger]. Excitement builds, press coverage proliferates, and the warning sounds: get on board now or be left in the dust [Peak of Inflated Expectations]. Companies rush to adopt the innovation, often with a heavy investment—and then, when the promised bounty doesn't appear as quickly as anticipated, there's an equivalent rush to bail out [Trough of Disillusionment]. Down the road—sometimes years later—widespread acceptance of the innovation's true value takes hold [Slope of Enlightenment], and it becomes a part of everyday business [Plateau of Productivity].

Gartner publishes over 75 hype cycles a year for their customers and released a 2010 Hype Cycle Special Report covering 1,800 technologies. Gartner advises companies about how and when to adopt technology, and there are different pros and cons to adapting a technology at different stages of maturity: adopt early to seize a competitive advantage, but often at significant cost; adopt late at minimal cost but merely to regain parity with competitors.

What the Hype Cycle Is

  • A representation of the different stages of social reaction that many technologies go through. Reaction differs as a technology moves from use by early adopters, through the chasm and to mainstream adoption.
  • A reminder that what the media is talking about is often way ahead of where the market is. Far more of the market talks about social media market research than practices it, for instance.
  • Fun! Well, if you like this sort of thing. (And I do, obviously.)

What the Hype Cycle Isn’t

  • An objective assessment of current media reaction to a technology. It’s a subjective judgment of the volume, sentiment and influence of coverage of a technology by news media, social media and thought leaders.
  • A one-size-fits-all curve and timeline. Technologies proceed through the stages at different rates; you can’t simply say “it’s been two years since mobile research platforms were introduced, therefore they’re at the Peak of Inflated Expectations.”
  • Hype Cycle book coverA sign that all technologies achieve lasting success. Gartner does forecast that some technologies will be “obsolete before plateauing”. Technologies always find an eventual use, but it might be on a very small scale (see Tools Never Die). For instance, the much ballyhooed era of pen computing seems to have plateaued as a component of credit card readers that record a digital signature – not at all the transformational technology that was envisioned.
  • A cycle for an individual technology. It’s not a cycle for the technology being covered, which never jumps back to the beginning; at best, a technology may spawn spin-offs that start at the beginning of the curve. Instead, the hype cycle is a cycle in the sense that thought leaders always move on to something new to hype.

Gartner’s hype cycle framework is valuable for researchers for two reasons: first, it shows the social reaction to new technologies and product categories over time; second, it can help inform a more measured assessment of new MR technologies themselves (more on this in the next post, Hyping Research Methodologies).

Mastering the Hype Cycle: How to Choose the Right Innovation at the Right Time, by Jackie Fenn and Mark Raskino, provides much more detail.

Comments

I like it, hard to tell where you are unless you're looking backwards. I was thinking about text analytics when looking at it. 
 
With text analytics I'm wondering if we aren't in the Trough of Disillusionment and beginning to climb upwards. But to be honest I'm not sure. That's where I am personally anyway ;) 
 
Curious to hear what other people think
Posted @ Wednesday, March 16, 2011 4:26 PM by Tom H. C. Anderson
I think most people still have inflated expectations for text analytics, as I show in this chart. I haven't talk to too many who are disillusioned, except for folks like you are on the leading edge of applying it to market research.
Posted @ Wednesday, March 16, 2011 4:47 PM by Jeffrey Henning
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