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jeudi 30 juin 2011

Seeding Strategies for Viral Marketing: Targeting Opinion Leader or not ?

Viral marketing

Do you remember "The Tipping Point", Malcolm Gladwell's best-seller ? I'ts about how trends work. Gladwell writes : "In a given process or system, some people matter more than others". In other words, people like opinion leaders are the "spark behind any successful trend".

So, marketers argue that targeted viral campaigning is more effective than good old mass marketing. They spend a billon dollars a year targeting precious influentials.  Are Klout or PeerIndex our future tyrants? It is clear that word of mouth (WOM) have strong influences on the success of viral marketing campaigns. But, is it useful to target key people, like opinion leaders, (ie. two-step flow model hypothesis) or not ? Does a random process works as well (network model structure)? More precisely, what is the optimal seeding strategy?

 Two-step flow model             vs          Network model of influence

Watts and Dodds (2007) tell us that people most easily influenced have the highest  impact on the information diffusion. They recommend  targeting a critical mass of influenceable people, rather than influential. Their conclusion is "Under most conditions that we consider, we find that large cascades of influence are driven not by influentials but by a critical mass of easily influenced individuals. Although our results do not exclude the possibility that influentials can be important, they suggest that the influentials hypothesis requires more careful specification and testing than it has received

A forthcoming article from Hinz and his colleagues (*) revisits this question. They compare four seeding strategies through one field experiment (a social platform like Facebook) and one real-life viral marketing campaign involving more than 200,000 customers of a mobile phone service provider. They use a sociometric method for identification of opinion leaders, that is respondents are asked to name the people they turn to for advice.

What is the best seeding strategy ?

First of all, their empirical results show that the best seeding strategies is targeting central opinion leader ("hub"). It can be up to eight times more successful than other seeding strategies.

Secondly, peripherical leaders  (« bridges ») are a powerful second best, because their influence is higher than random seeding.

What is the process behind this phenomenon ?

Why ?

Central opinion leaders constitute attractive seeding points because they are more likely to participate in viral marketing campaigns.

Moreover, these highly connected individuals also actively use their higher reach (ie. message diffusion on a higher number of person)


Central opinion leaders do not have more influence on their peers (ie. to make others to participate) than do less well-connected individuals.

Managerial implications

Marketers can improve the effectiveness of their viral campaigns by targeting central or peripherical opinion leaders (via sociometric method). Hinz et al. add : "Adding metrics related to social positions to customer relationship management databases is likely to improve targeting models substantially"..

And now our question is : how to identify an opinion leader in a social network, like Twitter or Facebook ? Klout or Peer Index metrics ? Self-designating method ? Sociometric method ? Results from Iyengar, Van den Bulte and Valente tend to promote sociometrics rather than self-assessment methods.

But no researcher has yet compared Klout or Peer index with traditional method...

(*) Oliver Hinz, Bernd Skiera, Christian Barrot & Jan U. Becker, Seeding Strategies for Viral Marketing: An Empirical Comparison, Forthcoming: Journal of Marketing, scheduled: January 2012.

vendredi 24 juin 2011

Co-creation : Work with Lead-users (*)

 Who are they ?

Lead-users are interesting for co-creation projects,  because they have two main characteristics (Von Hippel, 1986):
  • Ahead of the trend. These consumers present strong needs will become general in a marketplace months or years in the future.
  • Expect high benefits from innovating. They attempt to fill the need they experience and they can provide new product concept and design data as well.

Recent studies include new attributes to the original lead-user definition, such as technical expertise (Lüthje, 2004), community-based resources (Franke et al., 2006), early adoption of new products (Jeppesen and Laursen, 2009), opinion leadership (e.g., Ozer, 2009) and motivation (Bilgram et al., 2008). 

Taken in combination, these attributes lead to varying conceptualizations and as a result, the construct might be differently measured. In terms of psychometrics, these evolutions raise serious problems for measuring a fluctuant concept.

How to identify them ? 

Nevertheless, five methods exist. Unfortunately, research can't determine if they are convergent or divergent, but many works are in progress towards this goal.

This process relies on the ability of people with a strong interest in a search topic to know of others who are more expert than themselves (Lilien et al., 2002; Von Hippel et al., 1999). This approach offers many benefits since it allows “to reach the top of the pyramid” with a reduction of 71.6% of the search effort relative to mass screening (Von Hippel et al., 2009). Furthermore, it gives the opportunity to incorporate learning at each step of the process and to cross domain-specific boundaries (Poetz and Prügl, 2010). However, this strategy is still laborious because it seems to be efficient only when a small group of people know each other well (reputational information is needed) and have knowledge and serious interest in the topic.

Broadcast search
Firms who want to solve R&D problems externally with an open invitation to participate in providing new ideas use this solution. Broadcast search relies on a self-selection of the solvers which allows an access to (1) “core” problem domain experts and (2) experts with varying fields of expertise (Jeppesen and Lakhani, 2010). Weaknesses of this method are mainly the high search costs-because of the platform for enabling innovation and the awards for the best submissions- and the reliance on the self-assessment of the solvers.

Social networks and on-line communities
One must search consumers engaged in online communities.  Many consumers could engage in co-creation activities because they want to interact with other likeminded consumers  : "Blogs, bulletin boards, and joint collaboration spaces support interaction between participants. Community functionality enables participants to work jointly on problems and create solutions incorporating more than just the summation of each individual’s ideas and knowledge"(Füller, 2010).

Because lead-users were attracted by online environments for innovative activities and knowledge sharing (Füller et al., 2009; Jeppesen and Laursen, 2009), it's possible to obserserve and analyse these communities (Kozinets, 2002). Since there is an accumulation of lead-users within these environments, there is a growing interest in applying this solution for their identification (Belz and Bombach, 2010; Bilgram et al., 2008). However, even if netnography is a promising method, it relies on the researcher’s assessment (self-interpretation). Another limitation is linked to the missing part concerning the real-life acts of these users.

Screening via self-assessment
This method relies on the test of a large sample of users who self-assess themselves via questionnaires. Those who score highest are identified as lead-users. Several researchers have developed scales to screen a large and unknown population.  This strategy is generally preferred to the others for many reasons. Screening allows (1) easy access to the sample (via face-to-face, e-mail or telephone surveys), (2) rich data collection and analysis and (3) gain time. 

(*)  Post based on : Hamdi L et Vernette E. Identifying lead-users : validity evaluation of four self assessment scales, communication at the Open and User Innovation Workshop, Vienna, July 4th-6th, 2011.

References : See our selected Lead-user Bibliogaphy

mardi 7 juin 2011

Social networks and Opinion Leaders : two keys for adoption of new products

A recent article published in Marketing Science (2011 March-april), by Iyengar, Van den Bulte et Valente gives us some interesting highlights about opinion leadership and network.

Main research questions

1- Does word-of-mouth in social networks really affect how quickly members (hereafter physicians) adopt a new product (ie. a new drug against viral infection) ?
 2- Do actual opinion leaders exist and can one identify them ?
3- Where are good seedings points for a viral marketing campaign ?

Two measures of opinion leadership

1- Self-assessment opinion leadership scale (adapted from Childers, 1986, Journal of Marketing Research) : six questions for self-reported opinion (on a semantic differential scale)

Q1: In general, do you talk to other doctors about (viral infection) : 
Never — — — — — —— Very Often
Q2 : When you talk to your colleagues about (viral infection), do you : 
Offer very little information— — — — — ——Offer a great deal of information
Q3: During the past 6 months, how many physicians have you instructed about ways to treat (viral infection) : Instructed no one — — — — — ——Instructed multiple physicians
Q4 : Compared to your circle of colleagues, how likely are you to be asked about ways to treat (viral infection) ? Not at all likely to be asked— — — — — ——Very likely to be asked
Q5 : In discussions of (viral infection), which of the following happens more often?
Your colleagues tell you about treatments— — — — — ——You tell your colleagues about treatments);
Q6 In general, when you think about your professional interactions with colleagues, are you
Not used as a source of advice— — — — — ——Often used as asource of advice

2- Sociometric leadership (centrality network = indegree)
How many times a physician have been named by his or her colleagues as "someone with whom they feel confortable discussing" about treatment, or "someone to whom they typically refer patients"


Physicians from three large US cities: San Francisco (SF), Los Angeles (LA) and Los Angeles  (NYC). Response rate varie from  San Francisco (SF) (44.5 % = 150 respondents) Los Angeles (28.9 % : 197 respondents) Los Angeles (24.3 % : 284 respondents).

Within sociometric condition, the 67 respondents in SF generated 37 unique nominees for discussion and 24 unique nominees for referral. In LA, the 57 respondents generated 38 and 24 unique nominees, and in NYC the 69 respondents generated 43 and 22 unique nominees. 

For self assessment measures, the average score was closed to 26 points (mean = 4,5)

Main Results

- Correlation between the two leadership measures are significant (p < .001), but rather average : .45 for SF sample, .33 and .41 for or LA et NY samples.

- Correlation between early adoption and each measure of opinion leadership were stronger for sociometric measure (25%) than for self-evaluation leadership measure (11%).

- Evidence of contagion was found over network ties, even after controlling for marketing effort and arbitrary system-wide changes. Moreover, adoption is affected by peers’ usage volume, rather than by whether peers have adopted or are prescribing. 

 - Concerning the opinion leadership measures, authors find that self-reported leadership and sociometric leadership are distinct characteristics. More precisely "(i) they are weakly correlated, (ii) the tendency to adopt early is more pronounced for sociometric than for self-reported leaders, and (iii) self-reported opinion leaders are less responsive than others to their contacts’ behavior, whereas sociometric opinion leaders are not differentially responsive. "

-  Self-assessment measure of leaderhip does not equals sociometric leadership. Sociometric leadership was associated with early adoption even after controlling for contagion, and sociometric leaders were equally sensitive to contagion as non-leaders. Sociometric opinion leaders are also opinion followers, but self-assessed opinions leaders are not. Why ? These two measures probably tap some different underlying concepts : sociometric would be closed to the original leadership essences, self-assessment would rather measure self-confidence than true influence.

Two main marketing advantages for targetting opinion leadership:

1 : the “stand-alone” customer lifetime value (CLV) of opinion leaders will be higher than of other people because they tend to be early adopters and heavy users. 
 2 : their “network” value may be higher : they reach more people and also, because there are early adopters and heavy users, they influence others sooner and more effectively than less connected people.


1- Network ties affect the adoption of a new product
2- Focusing on opinion leader is worth of value
3- Sociometric would be a more valid measure of leadership

Read more

Iyengar R, Van del Bulte C and Valente W, How social networks and opinion leaders affect the adoption of new products, Marketing Science, 30, March, April, 195-212

mercredi 1 juin 2011

Insane Human Curling : Inside Bic Flex Experience

After the provocative viral ad  from Monminoutoudoux (Veet), a more conservative campaign from Bic. Still thinking that curling is a boring sport ? It's time for you to try human curling. Thanks to BIC Flex 3 Razors...


1 820 066 views on You Tube

Launched on april 11, 2011 in  France, campaign has been spread in Europe during May.

Agency: BUZZMAN (also see "shoot the bear or not")
Spot: Keith Schofield

With an extra bonus advergame : you can experience by yourself the Human Curling game : You only need a keyboard (space bar) or a webcam. Enjoy it !

Curling vs Bowling  ? A beauty Bowling 

A commercial from WAM Hair Removal: 


Beauty Bowling (180 000 views on You Tube)