In our survey we have a question asking people how often they are asked for their opinion on a range of products/services. We call this the Influencer Power. People who score high on that variable are possibly a good target for marketing campaigns.

My goal is to identify relations existing among these variables to build a more rounded picture of the people in our target audience rather than just looking at tiny single aspects of them.

Basically I’m looking for possible patterns in the answers to the “Influencer” questions. People who are influential in more than one category.

After some calculations I found the following profiles:

Group 1 “The home provider“. Influential in Grocery products (food); Snack Products; Grocery products (non-food); Soft drinks; Fast food; Alcoholic drinks.

Group 2 “The IT geek“. Influential in: Computers; Technology/gadgets; Mobile phones; The internet; Games consoles; Automobiles/Cars (but it has some influence in Music, Movies and sports too).

Group 3 “The Cultural butterfly“. Influential in: Books, Films, Skincare/haircare/beauty products; Music; Fine arts/Culture; Fashion/clothing; Celebrity news/Gossip; healthcare/pharmaceuticals and Food/restaurants.

Group 4 “The CEO“. Influential in: Business; Politics; Financial products; Environmental issues; Sports and Travels/Holidays (but it has also a quite strong influence in Cars and Culture.)

These groups show us how different product categories are correlated with each other and how opinion leadership is distributed. It’s not hard to imagine a gender, an age or even a style of life for each of these profiles so let’s go on with some basic demographics to further describe them.

In the table above we see that:

  • The IT geek is most likely to be a young single male.
  • The Cultural butterfly is a young educated woman.
  • The CEO is a wealthy, educated aging man
  • The Home provider is just slightly more likely to be a married female in her thirties than anybody else.

You might think this is not really surprising but actually, seeing such a structure in a sample covering 18 countries across the world is quite a statement about how globalized we really are.

Now let’s have a look at some key web behaviours for these influencers categories.

Again, The scores on these online activities largely confirm our common sense expectations.

  • The IT influencer scores high in almost all web activities. He is the king in our survey.
  • The Business influencer is likely to use Twitter, Feed readers and is probably a content producer himself. He is probably using Skype but not the text chat.
  • The Cultural butterfly influencer is a blogger and micro-blogger; (S)he uses the web mostly as an entertainment tool.
  • The Grocery Influencer is overall the less involved with the online world. He is probably too busy managing his household!

What does this mean for your marketing campaign?

It means that if you’re selling grocery products, you probably won’t be able to reach your key influencers via social media but you might still want to invest in Youtube because online videos show very little differences across influencers (they appeal to a wide, unsegmented audience).

Instead, if you are selling financial products you might want to focus on blogs and micro-blogs. Same if you’re in entertainment or fashion or culture (just be sure to choose the appropriate blogs and Twitter channels!)

Needless to say, if you’re in the IT, social media marketing should be your daily routine.

Note that like any statistical procedure, the factor analysis is an approximation. The numbers above are scores, not percentages nor market shares. They only give an indication of how each factor differs from the others. This analysis was based on 18 markets data. Single markets may significantly differ from each other and from the world average. The factorial data reduction, by its nature, involves some loss of information. Not everybody can be described using those four factors and no business decision should be based solely on one statistic.

2 Schooling until age 18 3 Trade / technical school or college 4 University 7% 5 Post graduate 2 In a relationship 3 Married 4 Divorced / widowed
  Home provider IT Geek Metrosexual CEO
i1_1 Income – Top 25% -1% 4% -17%
i1_2 Income – Middle 50% 3% 3% -1% -1%
i1_3 Income – Bottom 25% -2% 7% 2% 29%
q2 Gender 1 Male -8% -28% 22%
2 Female 14% -36% 36% -22%
q4 Age Groups 2 16-24 7% 23% -22%
3 25-34 8% 10% 2%
4 35-44 -1% 1% -7% -1%
-5% -15% -15% 12%
6 55-64 -21% -26% 22%
q6 What best describes your final level of education? 1 Schooling until age 16 -7% -36%
1% -11% -25%
-1% -3% -4%
-1% 12% 12%
3% 4% 14% 37%
q7 What best describes your current marital status? 1 Single -3% 15% 10% -15%
1% 2% 13% -6%
2% -7% -11% 13%
-3% -28% -4% -4%

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