marketing cascades
DESCRIPTION
Charlie Brummitt Just gave a great presentation to our office here at Universal McCann. While mainly conceptual, here are a few key points helpful to ad-agencies: Key Takeaways of the day: 1. Don’t waste your money on “Influencers”: The key to product adoption is not to pay large fees for Influencer promotions (i.e. celebrities or high profile bloggers), but rather to heavily target early adopters on multiple new-media channels. a. Each individual has a unique threshold of how many people in their network need to use a product before they will adopt it themselves. By targeting those with a low threshold who are likely to try new products without much persuasion, you can seed adoption across multiple networks at greater mass to reach those with higher thresholds b. Influencers (i.e. celebrities/high Klout users) can generate slightly higher user adoption, but not enough more than early adopters to justify huge fees. 2. Targeting Early Adopters: Early adopters tend to share very similar character traits by brand. a. Analyze archetypes of early adopters as opposed to all adopters to better target users during a product launch 3. Apply tactics on multiple new-media sites simultaneously to exponentially increase adoption. a. FB, Twitter, Pinterest, etc. campaigns are too often in silos. If a user sees friends from different networks promoting the same product, it exponentially increases their potential to purchase. Focus more on measuring these initiatives as a collaborative whole through mixed-media modeling.TRANSCRIPT
Threshold cascades for marketing
Charlie BrummittUniversity of California, Davis
Graduate Group in Applied MathPresenting work by others and joint work with
K.-M. Lee, K.-I. Goh (Korea University)
Soundbites
1. Target the easily influenced.
2. Targeting influentials probably not worth it.
3. Use new media. (Even a little bit.)
Threshold cascade model• A large group of individuals must make a
decision between two choices A, B.
• Examples:Do I buy an Android instead of Apple phone?Do I use Charles Schwab or not?
• Probability a person i chooses B over A increases with # of i’s contacts who have chosen B.
Reasoning: utility increases with # users, compatible technology, recommendations, influence.
Evidence for threshold model
• Kotler (2000): 60% of 7000 European consumers influenced to buy a new brand by family and friends
• Jupiter Communications (1999): 57% of people visit a new website due to personal recommendation (highest influence)
Live Journal DVD purchases
Example: Joe buys an iPhone once ≥ 20% of his friends have
Joe activates
Common choice: hard
thresh-olds
3 of 5 friends chose B
Joe
3
5> 20%
1. Start with a social network(e.g., everyone has ≈ 5 friends, chosenrandomly)
(or use a real social network)
2. Initially activate a few random people (seeds)
“early adopters” “given free copies”
3. Run the cascade dynamictill no one can activate
4. Final cascade size
here: 70%
How cascades
work
Example: Joe buys an iPhone once ≥ 20% of his friends have
Joe activates
Common choice: hard
thresh-olds
3 of 5 friends chose B
Joe
3
5> 20%
What affects cascade size:
1. threshold: % of friends
needed
2. Number of friends
What affects cascade size:
1. threshold: % of friends
needed
2. Number of friends
2 4 6 8 10z = average
number of friends
1cascade size r
need enough interactions
too many interactions: difficult to get enough of your friends to activate
cascade window
2 4 6 8 10z = average
number of friends
1cascade size r no cascades
z = 1 z = 3 z = 7 z = 9
average
Conclusion: more ads & influence → harder to
convince them
Influentials hypothesis
= influentials = people who influence their friends (not celebrities, formal leaders)
two-step flow of communication from media to influentials to everyone else
(Katz, Lazarsfeld 1955)
cascades driven by a critical mass of easily influenced people
Influentials not that importantDefine influentials: top 10% of influence
Influentials not that importantDefine influentials: top 10% of influence
Watts, D.J. & Dodds, P.S. Influentials, networks, and public opinion formation. Journal of Consumer Research (2007).
relative influence
relative cascade
size
influentials trigger slightly larger cascades
but not as much as their relative influence suggests.
Conclusion: don’t overspend on tiny fraction. Target the easily influenced.
Cascades are driven by “easily influenced people influencing other easily influenced people.”
few interactions, low threshold
Hyperinfluentials, communitiesConsider hyperinfluentials, who
influence way more people
But these hyperinfluentials are difficult to convince.
Hyperinfluentials, communitiesConsider hyperinfluentials, who
influence way more people
But these hyperinfluentials are difficult to convince.
People belong to groups. Many of our friends are friends.
But influential people tend to interact with influential people (assortativity)
and are difficult to influence.
Focus on easily influenced people.
Conclusions on influentials hypothesis
Watts, D.J. & Dodds, P.S. Influentials, networks, and public opinion formation. Journal of Consumer Research (2007).
• Influentials less important than generally supposed
• A critical mass of easily influenced people
• The particular people who cause cascades are likely due to chance.
• Marketers: if social influence is important, target easily influenced people.
colleagues friends
family
• 4 of your contacts bought a Windows 7 smartphone
• How likely will you buy it, too?
Multiple kinds of influence
• Different social spheres
Brummitt, Lee, Goh (2011) arXiv:1112.0093
k1 = 3,m1 = 1 k2 = 4,m1 = 2
max{13
,1
2
} > R ?
work colleaguesTwitter friends
Go out for drinks with colleagues. 2 of 4 bought a
Windows 7 phone. Will I buy it too?
Rule: I’ll buy it if large enough % of colleagues have. Or enough friends, enough Twitter followers, etc.
Multiple kinds of influence
Effect: large cascades easier.
Tool for marketers:Advertise even a little in new media
Facebook is crowded.
Tool for marketers:Advertise even a little in new media
Facebook is crowded.
Add another way to interact (e.g., Instagram).
Sparse layer can spark a cascade in the dense
layer
→ Viral marketing campaigns more effective with each new medium: Google AdWords, Twitter, blogs, forums, iPads, Pandora...
Stubborn people
• What if people aren’t so easily influenced by just one social sphere?
• Example: I won’t buy a Windows 7 phone unless >10% of my friends and >10% of bloggers whom I follow buy one.
• Suppose a fraction q of people are easily influenced (need just one social sphere), 1-q of people are stubborn (need all social spheres)
Discontinuous jump in cascade size. Explosively viral.
0.0 0.2 0.4 0.6 0.8 1.0q
0.2
0.4
0.6
0.8
1.0q•H1L = q•H2L
0.0 0.2 0.4 0.6 0.8 1.0q
0.2
0.4
0.6
0.8
1.0q•H1L = q•H2L
z = 1 z = 4
q
ρ
average cascade size
fraction of easily influenced people
few friends many friends
Many interactions → abrupt jump in
cascade size
jump
Implications of
• Well-connected networks attain suddenly large cascades as people become easier to persuade (increase q)
• Viral campaigns either fail or flourish. Hard to predict.
• Example: qsmartphone app ≫ qcar, apps go viral more easily than Priuses.
• Globalization, technology → more connections & ways to connect → more explosively viral
• - Does the success of your marketing campaigns change smoothly or abruptly?- Is adoption more viral/explosive in electronic media?- How does adding new media affect marketing success?
0.0 0.2 0.4 0.6 0.8 1.0q
0.2
0.4
0.6
0.8
1.0q•H1L = q•H2L
q
ρjump
Thank you!
Charlie [email protected]/~cbrummitt/
Collaborators:Kyu-Min Lee, Kwang-Il Goh (Korea University)