Table of Contents
Scope and Themes
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- What you need to know
- Definition
- Data sources
- Consumer survey data
- Abbreviations
Executive Summary
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- Who are the Influentials?
- Demographic comparison of teen Influentials
- What inspires Influentials?
- Who responds to Influentials?
- Media channels that generate buzz
- Interest in online tools that can generate buzz
- Race and ethnicity
Insights and Opportunities
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- Delivering on fundamentals like price, quality and service is the key to generating positive WOM
- Creating dialogue is an important element of effective WOM
- Young affluents are key influencers
- The rise of multigenerational households could open up new WOM opportunities
- Maximizing the value of WOM and viral campaigns: Generating insights along with buzz
- A note for the auto industry and partners: WOM influences many customers, especially the affluent
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- Figure 1: Influence of word of mouth/advice from friends on vehicle purchase, by income, July 2007-September 2008
- Regulation on the way?
Inspire Insights
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- Universal Uncertainty
- What’s it all about?
- Specifics
- Implications
- Influentials
- What’s it all about?
- Specifics
- Implications
Creating Buzz: Case Studies of WOM and Viral Marketing
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- Facebook: Gifts with benefits
- The Obama Model: Riding the 2.0 wave to the White House
- Influencer Ads
- BzzAgent: Dunkin’ Donuts Latte Lite
- BzzAgent: Tropicana Pure
- Super Bowl Ads
- E*trade
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- Figure 2: E*Trade Shankipotamus ad, 2009
- Cash4Gold
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- Figure 3: Ed McMahon and MC Hammer Cash4Gold ad, 2009
- Carrotmob: The New Agency?
- Colgate Smiles
- BzzAgent: Barilla Tortellini
Who are the Influentials?
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- Key points
- Young adults, affluents and parents often provide WOM recommendations
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- Figure 4: Attitudes indicating influencers (mean), by age, January 2009
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- Figure 5: Attitudes indicating influencers (mean), by income, January 2009
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- Figure 6: Attitudes indicating influencers (mean), by presence of children in the HH, January 2009
- Social media tools lend young adults more influence
- New social media tools
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- Figure 7: Participation in WOM and social media activities, by age, January 2009
- Americans are wired for social expression
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- Figure 8: Social influence traits, by age, July 2007-September 2008
- Young adults more likely to report having traits that make them influential
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- Figure 9: Social leadership traits, by age, July 2007-September 2008
- Figure 10: Social leadership, by income, July 2007-September 2008
- Young adults more likely to keep up with and promote fashion trends
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- Figure 11: Fashion affinity, by age, July 2007-September 2008
- Young adults more likely to disseminate information about technology
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- Figure 12: Technology/information, by age, July 2007-September 2008
Demographic Comparison of Teen Influentials
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- Key points
- As teens mature, especially females, they tend to become more influential
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- Figure 13: Technology/information—teens, by age and gender, April 2007-June 2008
- The majority of girls aged 15-17 reported pro-WOM characteristics
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- Figure 14: Social leadership—teens, by age and gender, April 2007-June 2008
- Figure 15: Fashion affinity—teens, by age and gender, April 2007-June 2008
What Inspires Influentials?
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- Key points
- Price, quality and convenience among the most powerful drivers of WOM
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- Figure 16: Basis of product or service recommendation to others, by age, January 2009
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- Figure 17: Basis of product or service recommendation to others, by income, January 2009
Who Responds to Influentials?
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- Key points
- Young adults more likely to be influenced by WOM
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- Figure 18: Source of word-of-mouth recommendation leading to purchase, by age, January 2009
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- Figure 19: Source of word-of-mouth recommendation leading to purchase, by income, January 2009
Time Spent on Internet
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- Time spent on the internet climbs along with home entertainment
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- Figure 20: Time spent other than email on the internet in the last seven days, by gender, January 2009
Media Channels that Generate Buzz
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- Key points
- Television is the medium most likely to inspire respondents to tell others
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- Figure 21: Offline advertising/recommendation media and word of mouth, by age, January 2009
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- Figure 22: Online advertising/recommendation media and word of mouth, by age, January 2009
Interest in Online Tools that Can Generate Buzz
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- Key points
- Interest in most WOM ‘widgets’ is moderate or low within online population
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- Figure 23: Interest in advertising/promotions (mean), by age, January 2009
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- Figure 24: Interest in advertising/promotions (only 5 and 4 responses tabulated), top two box responses, by age, January 2009
- Men more likely to enjoy widgets
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- Figure 25: Interest in advertising/promotions, by gender, January 2009
Race and Ethnicity
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- Key points
- Asians and Hispanics somewhat more likely to act on WOM recommendations
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- Figure 26: Source of word-of-mouth recommendation leading to purchase, by race/ethnicity, January 2009
- Minorities more likely to recommend products they have seen in advertisements
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- Figure 27: Offline advertising/recommendation media and word of mouth, by race/ethnicity, January 2009
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- Figure 28: Online advertising/recommendation media and word of mouth, by race/ethnicity, January 2009
- Hispanics and Asian respondents more likely to report wanting game-related promotions
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- Figure 29: Interest in advertising/promotions (mean), by race/ethnicity, January 2009
- Black teens are often Influentials in the world of clothing fashion
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- Figure 30: Fashion affinity—teens, by race/ethnicity, April 2007-June 2008
Cluster Analysis
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- Influencers
- Who they are
- Opportunity
- Sharers
- Who they are
- Opportunity
- Non-Conformists
- Who they are
- Opportunity
- Cluster characteristics
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- Figure 31: Word of mouth clusters, January 2009
- Figure 32: Source of word-of-mouth recommendation leading to purchase, by word of mouth clusters, January 2009
- Figure 33: Online advertising/recommendation media and word of mouth, by word of mouth clusters, January 2009
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- Figure 34: Interest in advertising/promotions, by word of mouth clusters, January 2009
- Figure 35: Attitudes indicating influencers, by word of mouth clusters, January 2009
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- Figure 36: Basis of product or service recommendation to others, by word of mouth clusters, January 2009
- Cluster demographics
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- Figure 37: Word of mouth clusters, by gender, January 2009
- Figure 38: Word of mouth clusters, by age, January 2009
- Figure 39: Word of mouth clusters, by income, January 2009
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- Figure 40: Word of mouth clusters, by race, January 2009
- Figure 41: Word of mouth clusters, by Hispanic origin, January 2009
- Cluster methodology
Custom Consumer Groups
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- Affluent men and couples among the most influential
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- Figure 42: Lifestyle segments with WOM leadership traits, July 2007-September 2008
Appendix—Additional Income Comparisons
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- Figure 43: Online social media participation, by income, January 2009
- Figure 44: Technology/information, by income, July 2007-September 2008
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- Figure 45: Personal relationships, by income, July 2007-September 2008
- Figure 46: Fashion affinity, by income, July 2007-September 2008
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- Figure 47: Advertising affinity, by income, July 2007-September 2008
- Figure 48: Time spent other than email on the internet in the last seven days, by income, January 2009
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- Figure 49: Time spent (average) watching television in a week, by income, January 2009
- Figure 50: Online advertising/recommendation media and word of mouth, by income, January 2009
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- Figure 51: Offline advertising/recommendation media and word of mouth, by income, January 2009
- Figure 52: Interest in advertising/promotions (mean), by income, January 2009
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- Figure 53: Interest in advertising/promotions, by income, January 2009
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Appendix—Additional Gender Comparisons
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- Figure 54: Interest in advertising/promotions (mean), by gender, January 2009
- Figure 55: Advertising affinity, by gender, July 2007-September 2008
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- Figure 56: Social leadership, by gender, July 2007-September 2008
- Figure 57: Technology/information, by gender, July 2007-September 2008
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- Figure 58: Personal relationship, by gender, July 2007-September 2008
- Figure 59: Fashion affinity, by gender, July 2007-September 2008
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- Figure 60: Online social media participation, by gender, January 2009
- Figure 61: Source of word-of-mouth recommendation leading to purchase, by gender, January 2009
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- Figure 62: Time spent (average) watching television in a week, by gender, January 2009
- Figure 63: Influence of word of mouth/advice from friends on vehicle purchase, by gender, July 2007-September 2008
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Appendix—Additional Age Comparisons
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- Figure 64: Time spent other than email on the internet in the last seven days, by age, January 2009
- Figure 65: Time spent (average) watching television in a week, by age, January 2009
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- Figure 66: Influence of word of mouth/advice from friends on vehicle purchase, by age, July 2007-September 2008
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Appendix—Additional Race and Ethnicity Comparisons
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- Figure 67: Online social media participation, by race/ethnicity, January 2009
- Figure 68: Time spent other than email on the internet in the last seven days, by race/ethnicity, January 2009
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- Figure 69: Time spent (average) watching television in a week, by race/ethnicity, January 2009
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- Figure 70: Attitudes indicating influencers (mean), by race/ethnicity, January 2009
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- Figure 71: Social leadership—teens, by race/ethnicity, April 2007-June 2008
- Figure 72: Technology/information—teens, by race/ethnicity, April 2007-June 2008
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- Figure 73: Advertising affinity, by race/ethnicity, July 2007-September 2008
- Figure 74: Social leadership, by race/ethnicity, July 2007-September 2008
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- Figure 75: Technology/information, by race/ethnicity, July 2007-September 2008
- Figure 76: Personal relationship, by race/ethnicity, July 2007-September 2008
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- Figure 77: Fashion affinity, by race/ethnicity, July 2007-September 2008
- Figure 78: Influence of word of mouth/advice from friends on vehicle purchase, by race/ethnicity, July 2007-September 2008
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Appendix—Trade Associations
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