iCitizen 2008: Duncan Watts

DUNCAN WATTS Word of Mouth for the Real World

PEOPLE INFLUENCE EACH OTHER IN MANY WAYS
MARKETERS HAVE ALWAYS EXPLOITED THESE EFFECTS
Branding
Endorsements
Celebrities
“Ordinary people”
Product Placements
Social Proof
Being talked about in the media
SOCIAL INFLUENCE IN MARKETING

Research in 1950’s emphasized importance of personal influence
Trusted ties more important than media influence in determining individual opinions
Also found that not all people are equally influential
A minority of “opinion leaders” or “influentials” are responsible for influencing everyone else
Influentials, in turn, influenced by the media
Together, these findings led to the “two-step flow” of influence
Call this the “influentials hypothesis”
BUT OF WORD OF MOUTH IS SPECIAL

THE “INFLUENTIALS HYPOTHESIS” “ One in ten Americans tells the other nine how to vote, where to eat, and what to buy.” (Keller and Berry, 2003)

IT’S A GREAT STORY… = “ Social epidemics ... are also driven by the efforts of a handful of exceptional people” Gladwell (2000) Free!!

East Village Hipsters start wearing Hush Puppies, and they become popular again
Some unknown designer becomes famous when an actress wears his dress to Oscars
Jeff Jarvis complains about Dell on his blog, and suddenly there’s an uproar
A single patient in a Hong Kong Hospital jump starts the SARS epidemic
AND IT SEEMS TO EXPLAIN A LOT

“ Influencers have become the ‘holy grail’ for today’s marketers.” —Rand (2004) But grails are hard to find…

The Influentials Hypothesis is simple and appealing
A few special people (“Connectors,” “Mavens”) generate a huge impact
It is also seemingly prescriptive
“ Find the Influentials and Influence them”
It should work everywhere
It seems to explain so many things
So why is it so difficult to implement?
WHAT’S THE PROBLEM?

... but they operate in very different ways. Lots of kinds of people could be (and have been) called “influentials”...

If who is influential depends on circumstances, can anyone be an “influential”? Even ordinary people can be influentials in many different ways. Alpha Moms Connectors Brand Enthusiasts Mavens Trendsetters

Stories are important for making sense of things
“ Hipsters wore hush puppies and then other people did. Therefore hipsters made hush puppies popular”
What seemed mysterious is made to seem sensible, inevitable
But, Stories only ever “explain” events in hindsight
We only try to explain “interesting” outcomes
Hipsters wear clothes every day
Only need to account for one sequence of events
Hush Puppies might have caught on anyway
An explanatory theory also requires accounting for
Everything that might have happened, but didn’t
Everything that might have led to what did happen
To make use of social influence, we need theories, not stories
STORIES ARE NOT THEORIES

Some people are more influential than others
But no-one influences everyone
Influence is
Bi-directional
Distributed
Multi-step
A THEORY OF SOCIAL INFLUENCE

Computer simulations of influence networks
Whether or not influence can spread widely depends mostly on the network structure
If network permits spread, anyone can start something; and if not, no-one can
Influentials at best modestly better starting points than average people
Large cascades driven by “easily influenced individuals influencing other easily influenced individuals”
Not “influentials influencing followers”
SOME RECENT RESEARCH (Watts and Dodds, JCR, 2007)

No-one would claim that large forest fires are started by “special” sparks
Yet for social phenomena, we want to believe “special” outcomes are caused by special people
A network view of influence suggests that individuals who later seem influential may simply be accidents of circumstances
Obvious in hindsight, but not in advance
FOREST FIRES AND ACCIDENTAL INFLUENTIALS

Experimental study involving 15,000 subjects
Designed to test how Individuals are influenced by what others think
Subjects were shown a grid with MP3s from unknown bands
They listened to, rated and downloaded favorites
Behavior was tracked in several different “worlds” to measure social influence
MORE UNCERTAINTY: THE MUSIC LAB EXPERIMENT

THE MUSIC LAB SETUP

Individuals clearly influenced by the votes of their peers
Popular songs became more popular, and unpopular songs less popular, than in the independent condition
Social influence increases inequality
But also became harder to predict which particular songs would become popular
Social influence increases unpredictability
“Best” songs never do terribly and the “worst” never excel; but anything else is possible
EXPERIMENT RESULTS (Salganik, Dodds, and Watts, 2006)

When people influence each other, outcomes are inherently unpredictable . What we learn from the past is of little use in predicting or planning the future. No easy solution to this one. Be sceptical of holy grails and free lunches. But can identify some principles for operating that don’t depend on locating “special” people or having brilliant instincts. The Network Challenge: Radical Uncertainty

Aim for Easily Influenced masses over Influential Minority
“ Bored at work network” is millions of workers who share media, blog, and IM all day
Can make anything “go viral” if they like it
But hard to predict what they’ll like
Although quick, fun, and easy to share tends to do better
So generate lots of options and /or variations
Measure performance in real time
Redirect energy/attention to successful ones
Whenever possible, experiment
PRINCIPLE #1 MEASURE AND REACT

Most things will not “go viral”
Especially if your message is utilitarian, serious, and/or complicated
Relying on small number of influentials simply aggravates the unpredictability
Instead, target large number of ordinary individuals, and help them share message
Target “big seed” of 10,000 people
They recruit 5,000 extra people,
Those people recruit 2,500, etc…,
Eventually dies out, but get 10,000 extra in process
PRINCIPLE #2 DON’T COUNT ON “TIPPING”

Using ForwardTrack Software developed at Eyebeam
Tide Cold Water seeded with over 900K and got 40K extra
Oxygen Media turned seed of 7,064 people Into 30,608
No “tipping” but clear, measurable ROI
“ BIG SEED MARKETING”

“ Mullet Strategy”
Business up front, party in the back
Let a thousand flowers bloom,then pick the best
Huffington Post, Digg, etc.
“ DIY Influentials”
Pick the individuals who are already broadcasting your message, and make them influential
BuzzFeed.com is platform for detecting and directing buzz
PRINCIPLE #3 MANAGE, DON’T DICTATE

BuzzFeed embodies network thinking
Locate Buzz
Filter the Entire Web
Trend Detector
Crawler
Search
Manage Buzz Publish and Seed
Measure and React
Respond to Real Data
Search Engine Tracking
“ % Viral” Tracking
Widget Click Stats
The Web App:
Publish Aggregated Buzz
Widgets on Network
BuzzFeed.com
BuzzFeed Ads

Bad news is that complexity of influence networks means we can’t predict either what will succeed, or who will make it succeed
Good news is that we don’t need to
Build Portfolios - measure and experiment
Contagious Media - focus on the easily influenced
Big Seed Marketing - viral marketing without tipping
Mullet Strategy - try everything and promote what works
DIY Influentials - promote those who promote you
Main point is that network thinking replaces instinct
The more we can measure, the more this will be true
SUMMARY

REFERENCES
D. J. Watts and P. S. Dodds. Networks, influence, and public opinion formation. Journal of Consumer Research, 34(4), 441-458 (2007).
D. J. Watts and J. Peretti. Viral marketing in the real world. Harvard Business Review (May, 2007)
D. J. Watts. Is Justin Timberlake a product of cumulative advantage? The new theory of the hit record. New York Times Magazine (15 April, 2007)
D. J. Watts. The Accidental Influentials. Harvard Business Review , p. 22-23 (February, 2007)
D. J. Watts and S. Hasker. Marketing in an unpredictable world. Harvard Business Review , p. 25-30 (September, 2006)

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http://davidgillespie.wordpress.com	72
http://www.servantofchaos.com	57
http://www.futureofinfluencesummit.com	41
http://www.rossdawsonblog.com	17
http://feeds.feedburner.com	8
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iCitizen 2008: Duncan Watts

by Resource Interactive on May 28, 2008

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iCitizen 2008: Duncan Watts — Presentation Transcript