If you have ever read Malcolm Gladwell’s The Tipping Point, you will know what a perceptive and persuasive treatise on the viral power of social trends this book really is.  Through an eclectic set of superbly chosen anecdotes, Gladwell engagingly unveils this phenomenon, from the retro rise of Hush Puppies footwear to the disturbing epidemic nature of teen suicides.

But do such findings really apply to a brand’s advertising and marketing?  Can we see an outwardly perceptible relationship between the few, influencers who have the capacity to influence, and the many, general consumers of a brand or product.  If so, can we readily quantify that relationship?

To help answer this, we recently interrogated the word of mouth study, Talk Track, by the Keller Fay Group.  We found clear evidence that the relationship between influencers and general consumers talking about a brand varies by market category in quite a predictable relationship.

Each year, Talk Track asks 36,000 consumers about their daily word of mouth goings-on and how often and in what ways they talk about brands. Talk Track also classifies people by the size of their social network and the amount of advice they provide to others in a specific market category.  Consumers placed in the highest social network and category advice levels are called Conversation Catalysts, as an effective proxy for a category’s influencers.

Taking the fifteen market categories that Talk Track monitors, we can place them on a map to determine if there is a visual relationship between general brand mentions by consumers and Conversation Catalysts or influencers.  We call this type of map, the WOM Opportunity Grid (see Figure 1), and it shows a clear relationship between the two criteria:

Figure 1

As we can see, the map implies a connection between, on the vertical axis, a category’s share of total mentions (for all brands in all categories) and, on the horizontal axis, the penetration of a category’s Conversation Catalysts among the general US population.

The individual blue dots on the map represent each of Keller Fay’s 15 market category’s spanning the full range from Media & Entertainment to Household Products.  We can see the best line of fit, the regression line, as the dotted blue line that dissects the map, running diagonally from bottom left to top right.  And we can also quantify the relationship or fit between these two factors where correlation is 81%.   In other words, as conversation levels increases there is, on average, an 81% proportional increase in influencers and vice versa.

This map and its findings have two major implications for marketers:

1.     If a brand is to maximize its conversation potential, it is not enough to focus simply on creating that conversation with consumers, a parallel communications strategy should often be embraced for influencers.

2.     Where a brand and its category fall on the map is critically important for that brand’s conversation, face-to-face marketing and social media strategies.  Plainly, it is not a case where one overarching conversational strategy will fit all brands in all categories.  Brands in categories in the top-right hand quadrant, high mentions/high influencers, have a very different – and much easier – task to develop consumer conversation levels than products in categories in the lower left quadrant, low mentions/low influencers.

How do we identify and reach influencers?  For an influencers’ strategy, it not just a case of reaching them but actively nurturing them as well.  For example, the major media survey, MRI, has specific proprietary questions to identify what it terms category influentials.  Taking the travel category as an illustration, MRI indicates three magazines, Travel + Leisure, Condé Nast Traveler and Arthur Frommer’s Budget Travel, are particularly relevant at reaching travel influencers.  Online has similar opportunities such as Trip Advisor.  By proactively harnessing these media, one would not only aim to reach out to travel influencers, but also via competitions or promotions or other invitations to be involved, start to build a direct dialogue with them and establish a highly customized, relationship marketing strategy.

In such a short column, we can only quantify and explain the core issues.  Macro approaches and solutions that are individually tailored to a brand’s conversational aims and needs also follow some clear guidelines.  If you are keen to know more, I would urge you to attend to the Word of Mouth Marketing Association Summit on November 17-19.  Among others, Brad Fay of Keller Fay and I will talk about tangible and practical solutions to the issue of amplifying a brand’s conversation levels using the approach outlined here.

To gain a deeper appreciation of success and ambition, Simmons offers about 20 questions on the subject. UM’s marketing and communications survey, Media in Mind, which is linked to Simmons, expands this by a further 25 questions.  What can these 45 questions tell us?

Ambition in its archetypal sense is a young, primarily male characteristic.  Men under 35, especially those under 25, are twice as likely as the general adult population to agree with statements such as: “I like to have possessions others envy.” or “People are impressed with…the technology devices I use” and “…owning a luxury car….” Women under 35 follow a similar pattern except that retail therapy takes on an added dimension since they agreed they “like shopping at prestigious stores,” while Women 25-34, index highest on “I like having expensive jewelry or watches.”

If you are targeting a $250K+ “high earners”, owning a luxury car often appears to be a key status symbol.  It indexes at 286 among this group versus the general adult population.  No other success metric comes close for this income group.

Curiously, ambition and happiness do not appear to be the same personal mindset.  Just as being ambitious has an inherently younger male slant, being happy has an opposite older female bias. Media in Mind implies that, as you become older, happiness is more prevalent than ambition. This finding is corroborated by Barbara Stauch in her recent book The Secret Life of the Grown Up Brain. As Stauch observes: People feel better as they get older. They feel more in control and they feel grown-up and handle the stress of life. Not only is their judgment better, they actually feel more cheerful, and focus more on the positive than they did while young.

Yet what attitudes indicate or help make any of us feel happy?  For instance, would you agree with any of the following three statements:  a) I am satisfied with my, b) life I am very happy with life as it is and c) I am happy with my standard of living.

Chances are pretty high that you’d definitely agree with at least one of these statements, as do 77% of US adults.  If you’re lucky, you’ll be in the fortunate 10% that agree with all three.

We probed our Media in Mind database, and what distinguishes being happy can be encapsulated in four key attitudinal statements:

• I am good at what I do.
• If at first you do not succeed, keep trying.
• I am able to balance what’s important in life.
• It’s important to feel respected by my peers.

What is striking about this list is the need to maintain an equilibrium between a) a strong internal gyroscope focusing on what we actually do and what we need to do and b) the desire to balance that focus with other aspects of our life and gain positive feedback from others we value.

So what are the implications for marketers?

1. Actively treat our target prospects with respect.  We consistently see Americans culturally relate success and happiness to both self-respect and mutual esteem.  Social media only increases this expectation.
2. Assiduously align the brand’s product plan to our audience.  Avarice is clearly a trump card in marketing to young adults and some wealthier cohorts.  For example, if we’re in technology, making our device conspicuously cool is a major prerequisite for victory.
3. Encourage relevant feedback and interaction via user communities to help consumers feel reassured, reaffirmed and happy about their brand choice.

George Santayana, the Spanish-American philosopher, noted Knowledge of what is possible is the beginning of happiness.  That’s a seductive insight and I’d like to agree except I intuitively suspect that raw, unbridled ambition simply refutes the status quo of the possible.  And in their purest forms, ambition and happiness are probably quite opposite constructs.

Our media consumption patterns may be known in microscopic detail but the motivations behind those patterns are largely assumed.  This assumption results in the overlooking of small shifts in our aggregate media consumption patterns each year. Over time, these shifts can cascade into an avalanche of change that seems to come from nowhere.

For example, how many marketers still didn’t know what blogs were three or four years after the term was first used in 1999; or thought Twitter, created in 2006 and which at time of writing is at over 14 billion tweets, wasn’t an issue until quite recently; or to this day may never have heard of Gary Vaynerchuk, arguably the Paul Revere of the social marketing revolution.

In their monograph, Media Generations, Professors Block and Shultz of Northwestern University posited the view that our primary media habits are predominantly shaped by the media we experience at an early age.  They encapsulated this in the phrase: You are what you grew up with.  They expanded on the idea as follows:

…the experiences of childhood, especially in teenage years, impact the shape and course of later life…  That is, the way media and marketing communications are learned during childhood determines the patterns for the rest of one’s life, even though new media and technologies appear… Boomers use the Internet, but they use it differently than do Millennials who grew up with it.

The notion that exposure to a medium at an early age leads to an innate familiarity with that channel makes eminent sense.  Yet our implicit literacy of a medium probably stretches beyond our simply being immersed in that channel at an early age.  Focusing on the three mass media that have emerged since the middle of the 20^th century – TV computer and mobile phone – aka the three screens, we can unravel how each screen engages the various functions within our brain.

Neuromarketing proves the three screens of TV, computer and mobile phone are handled by the brain in quite different ways, ways that consumers cannot necessarily identify themselves. Our brain’s ability to process an experience is far more advanced than our ability to verbalize that experience. Neuromarketing reveals our brain processes an event at 300 to 500 thousandths of second after the experience whereas as our conscious brain, the thinking of which we’re all aware, starts to engage at about 500 thousandths of second and beyond.

At a recent Advertising Research Foundation meeting, Dr A.K. Pradeep of Neurofocus, a leading neuromarketing research agency, isolated the essential differences in how the three types of screen communicate.  By scrutinizing consumers’ precognitive responses, the responses before conscious thinking fully engages, Dr Pradeep was able to demonstrate the relative communications strengths of each channel:

• TV is superior for emotion and action
• Computer online is better for dynamic content and personal or private communications
• Mobile is excellent at helping drive memory

Part of the strength of TV and computer screens is that their larger size helps draw out “human elements and fine details.”  By contrast, mobile’s smaller screen demands an intensity of focus which can result “in a significant boost in memory retention.”

So if we can largely explain our innate media habits by the phrase You are what you grew up with, why aren’t we following this principle more assiduously in our industry media research? The main studies of both MRI and Simmons don’t track under 18s, so emerging media trends could still be missed. Even the groundbreaking Nielsen-sponsored Video Consumer Mapping Study, which looked at the consumer’s use of all three screens in great detail, didn’t include teenagers.  In contrast, Target Group Index, the major international multimedia study available in over 60 countries, routinely surveys individuals aged 15 and over, and in some countries as young as 12.

Shouldn’t the USA be quicker to embrace teenager-driven insights into burgeoning multimedia trends?

To assess the relationship between advertising and word-of-mouth, we constructed a regression model built specifically for the purpose.  The model tapped two syndicated data sources: Keller Fay’s Talk Track for word-of-mouth and TNS’s Media Intelligence for media spend.  We looked at two different advertisers, both of whom are UM clients.  Let’s call them Advertiser A and B.

Both Advertiser A and B are large brands who are household names.  Advertiser A has a distinct yet broad female bias while Advertiser B has a somewhat upscale and stylish appeal.  The two advertisers operate in different market categories and draw on advertising’s ability to help spur their business in markedly dissimilar ways.  Consequently as we might expect, advertising’s potential impact on their word-of-mouth, WOM, was also distinctly different for each marketer.

Extensive data interrogation revealed the most pragmatic way of correlating the two data sources was to create rolling three month averages for each data set, refined by some minor tweaks by channel.

For each marketer, we were able to determine a clear correlation between advertising weight and word-of-mouth.  For Advertiser A, it was 94% and for Advertiser B 89%.

Since the model included media spend, we could also establish advertising’s return on investment in building WOM.  Importantly, the model’s spend inputs were not based on total media spend but on TNS’s reported investment in each media channel.  In other words, not only could we see advertising’s overall effect in helping build WOM, but the model would also tell us which media were more effective.

Advertiser A’s unexpected result: dollar for dollar, women’s magazines out performed television by a factor x25!  Yes, for every $1 spent on women’s magazines, we would have had to have spent $25 to build the same WOM effect on TV.  This compelling finding triggered our curiosity to quiz this further – why were magazines so powerful for this advertiser?

Keller Fay’s Talk Track can trace specific WOM brand mentions down to an individual magazine.  We sought empirical evidence of brand mentions for Advertiser A at the individual title level that might corroborate the model’s findings.  Since the regression analysis was based on rolling three months data, we wouldn’t expect to see an exact match to the advertiser’s magazine schedule.  But by comparing Advertiser A’s brand mentions in over 30 magazines to each magazine’s individual reach of Advertiser A’s regular users, we saw a heartening correlation between the two of 78%.  Not quite proof positive, but good circumstantial evidence nonetheless.

Advertising clearly appeared to help Advertiser A build their WOM, and our model indicated that advertising helped generate up to 70% of the total WOM for that marketer.

Although we investigated many alternatives, we found the same approach also worked best in building a regression model for Advertiser B.  In summary, we were able to see a clear return on investment that differed distinctly by channel and reflected this particular advertiser’s broader based media strategy.   Since this advertiser is the market leader in a high interest category and whose quality products command a price premium, Advertiser B is explicitly less reliant on advertising.  Consequently, in this instance we saw that advertising generated 23% of the brand’s word-of-mouth, but this was wholly consistent with the role of advertising for this marketer.

As the media world has become more complex, consumer word-of-mouth has grown in importance.  Arguably, a key factor in this phenomenon is that each consumer has become their own integrator of what they see, hear and interact with.  Word-of-mouth is the consumer’s own output and interpretations of these aggregations.

Yet most word-of-mouth research studies, with the exception of Keller Fay, have a purely online perspective and focus on online conversations, postings and areas such as consumer video sharing.

While online conversation and social media monitors are invaluable in discerning consumer trends, none of them directly demonstrate the value of other media.  We need to continue to develop word-of-mouth tools which appraise not just digital media but the complete media communications spectrum.  As Lord Kelvin, the great pioneering 19^th century scientist, succinctly put it:  If you cannot measure it, you cannot improve it.

When we ask US online consumers how “trustworthy” they rate information typically provided by various contacts, a wide ranking emerges. Personal recommendations from family and friends scores highest at 6.7 out of a possible 10. Consumer online recommendations on sites such as Amazon score 5.7 By comparison, TV or magazine advertising merits only 3.7. At least advertising beats email spam, which scores a lowly 3.1.

But if online word of mouth is mushrooming in its online presence, how do we embrace it, particularly its most evocative online form — User Generated Content (UGC) — without falling into the classic traps feared by many. Fortunately, if we really want to incorporate WOM, there are ways to draw on research to ensure we can develop scalable and repeatable strategies.

WOM is deeply rooted in our culture: Americans do like giving their opinion both on- and offline. Tracking WOM across 22 product categories, we have found that 80% of Americans “often inform others on what to buy” in at least one of these categories. More intriguingly, we are seeing the emergence of the Super-Influencer – 30% of us inform others on what to buy for five or more categories.

Super-Influencers exhibit clear preferences in the subjects they like to talk about. At the broadest level, our analysis indicates Super-Influencers will tend to focus on one of two macro-topic groups, either: a) technology and entertainment or, b) more personal and household matters such a fashion, cosmetics, personal health and groceries. Similar smaller topic groupings occur throughout people’s WOM repertoires –people often like to talk to others on several related topics such as music and films, or children, homes and families.

The implication of these types of macro-topic groupings is actually quite profound. If we wish to activate a WOM or UGC strategy, we should avoid the pitfall of directly inviting consumers to create a specific response around our product. As Chevy Tahoe found out in 2006 in the USA, consumers rebuffed the marketer’s invitation to create UGC ads for the SUV, and instead they exploited it as a chance to attack the vehicle’s fuel consumption. As a result of this type of experience, the marketing industry is often hesitant to pursue WOM or related UGC consumer creation strategies.

Instead of inviting consumer responses on the brand directly, we should harness this type of customized WOM topic research to determine what other often seemingly-unrelated product areas do actively interest our consumers to talk to others. We could then include these other potential areas in a re-focused WOM or UGC activation strategy to emphasize our product’s proposition without necessarily talking about our product. In turn, this can unexpectedly broaden the interest and appeal of our brand.

An admirable case in point is ING Canada. A year ago, they ran a UGC competition on the theme of savings – but rather than being about bank savings and deposits , the competition was about any form of saving. Consumers’ UGC responses were diverse, humorous and creative. For example, they included a video about someone trying to save money by ordering a pizza where the pizza was free if it was not “delivered to your hands” in 30 minutes. So the diner-to-be deliberately refused to physically accept the pizza when the delivery guy turned up at his door and a very humorous skit ensued.

It is these sorts of surprising approaches where WOM and related UGC strategies will ultimately succeed because they not only arouse consumers’ genuine curiosity and invite an authentic response that isn’t transparently self-serving to the needs of the brand, they also provide a broader-based forum to interact with the brand and other fans.

Essentially, he posited that any reasonably intelligent intern could join a media agency and hopefully, after a couple months, he or she would fully appreciate basic media planning concepts such as reach and frequency.

But as he followed through to his punch, he doubted that even if the intern stayed at the agency a couple of years whether she or he would be able to nail a crisp definition of engagement because it is so multifaceted and indistinct a concept.   It was then I realized the enigma of engagement: Every media person knows what engagement is, but nobody can put it in terms which everyone else can agree on.

Subsequently, I came across a succinct definition of engagement by Dr. Carl Marci of Innerscope.  He defined biological engagement as:  attention + emotion = engagement.  For me, the strength of this definition is in its simplicity, yet it can have a universal application across media.

Moreover, Dr. Marci revealed how, in a lab setting, he could measure engagement by a combination of biometric proxies such as eye-gaze, heart-beat and galvanic skin response.  For example, someone can watch the same TV ad in different program environments and as a consequence be responsive at varying levels of intensity to the ad depending on the type of program being watched.

We can also pinpoint evidence of consumer engagement in the real world via a panoply of robust surrogates.  One of the more palpable is the increased level of active consumer interest when using multiple types of screens: for example TV, computer and Smartphone.

In the Spring of this year, UM and AOL completed an exclusive joint venture research endeavor exploring one of the most inspiring areas of the digital media revolution, Smartphones.  Entitled Smartphone, Smart Marketing, this extensive study harnessed qualitative diary panels, ethnographic study and quantitative research to interrogate the opportunities in this area.

A key area we probed was media meshing.  Media meshing extends beyond what is called concurrent media exposure – it is when the consumer is viewing more than one media channel specifically to look at particular content so that you can be fully immersed in the topic.  Owing to their ability to provide instant information gratification anywhere the user chooses, Smartphones are today’s ultimate media meshing tool.  For instance, if you want to check out an actress you’re watching at that very moment on TV, a Smartphone can parade to you everything known about her in an instant while you remain in your armchair and continue to catch glimpses of her.

Smartphone, Smart Marketing highlighted 67% 18-34s were more apt to look at similar content on their Smartphone while viewing another medium.  One of the reasons why receptivity is amplified when Smartphones are an integral part of the communication mix is that only 13% of consumers agreed they were “completely focused” when watching TV but this doubled to 27% when viewing their Smartphone.

Similar findings that substantiate the power of media meshing and its influence on engagement have been seen from organizations as diverse as MTV and Keller Fay.  These studies underscore that viewing related content on two screens or more increases viewer receptivity and spurs them to talk about the topic they were watching.

The industry has taken a long time to come to terms with engagement.  In our industry’s characteristically faddish manner, the concept has probably lost many of those who might have been originally enticed by its promise of more effective communications.  But now we can understand and measure it both in the biometrics lab and the real world.   It’s time to re-engage with engagement.

-by Graeme Hutton, director of consumer insights

The former Forbes editor and current CNBC anchor’s intense attachment to his smartphone is not a laughing manner for at least 19 million people in the States today. UM and AOL’s “Smartphone, Smart Marketing” report–researched jointly with Questus–placed roughly 10% of all of the US’s mobile subscribers in the “lead users” category that could also be used to describe Kneale. And with the amount of technology–from e-books to site-specific applications–taking mobile phone functionality to new limits, that number is growing every day.

If one out of every seven minutes of media consumption today is done via a mobile device, any marketer not attempting to engage with the growing number of consumers in the mobile arena could be missing out, big time. The “Smartphone” report found that more than one-quarter of smartphone users describe themselves as “completely focused” when using their mobile devices, as opposed to 13% who would describe themselves that way when watching TV and the 19% and 17% who would describe themselves that way while reading a magazine or newspaper, respectively.  AND, almost 40% of the 1800 we surveyed have taken action from a mobile ad, suggesting that mobile advertising is at the cusp of driving new consumer behaviors.

Users know a seismic shift in advertising is coming — c’mon, how long would you last without your iPhone–and they are excited about it.

Want to know more about how consumers are using their smartphones and how marketers and reach them in a relevant and engaging way? You should reach out to UM for the “Smartphone, Smart Marketing” report.