The internal impulse to check our messages at such challenging times is fostered by the brain. By checking our messages in such circumstances, the brain rewards our apparent furtiveness with a minute release of dopamine. Dopamine is a hormone and neurotransmitter related to the pleasure system of the brain. In large doses, it can provide a real high.

Intrigued by this phenomenon, we approached UM’s standing panel of academic psychologists about the concept of Always-On. These psychologists are typically U.S. professors and other leading practitioners in their field. We wanted to solve the following riddle: How do we break through the obstacles created by Always-On and reach consumers in the most compelling and convincing way?

Our expert panel brainstormed the issue of Always-On and its implications for both brands and media marketing. Overall, we identified ten key areas essential to overcoming the barriers of Always-On which in summary are:

1. Celebrate the brand’s excellence. As one psychologist astutely noted, in a world of Always-On, it is easier for the digitally savvy to find strong brands. Once found, it is cognitively easier to stick with a winning brand that puts consumers first. As Robert Passikoff’s noted in his book, Predicting Market Success, “Brands are competing to meet or exceed customer values first, and against each other second.”
2. Tap into the key emotional needs the product satisfies. In other words, “Don’t sell the steak, sell the sizzle” or as Harvard Professor Theodore Levitt once famously exclaimed, “People don’t want quarter-inch drills, they want quarter-inch holes.”
3. Ask not what your consumer can do for you, ask what you can do for your consumer. Build the brand and its inherent consumer rewards for the longer term. Over time, consumers will immediately associate the brand with this powerful value that will break through many Always-On issues.
4. Ensure message simplicity. Make the consumer’s decision process of getting to ‘yes’ easy, and the emotional benefit clear.
5. Assess reward and loyalty systems. Added-value offers and promotions are very seductive to consumers in the short-term and can help marketers achieve break through when and where they need it most.
6. Consider personal, human icons. e.g. Kim Kardashian or Dr Oz. Here the idea is to humanize the communication by appointing a well-known personality as a focal point. Anthropomorphization of the brand communication helps provide personal relevance.
7. Request user feedback and respond back directly to the consumer. Social media fits this solution like a tailored-made glove. It provides scale and an immediate platform for consumer interaction. Apple has also shown an alternative approach by having Apple stores which offer advice as well as sell their product. iTunes will genuinely answer any account question within 24 hours.
8. Be Green or consider a cause that is close to the brand’s heart. Besides classic brands, cause marketing can work for brands which are less conventional but still evoke high consumer interest.
9. Pursue word of mouth and event marketing. Face-to-face marketing is the natural antidote to ‘Always-On.’ This type of marketing not only allows a deeper, personal connection with consumers, but it can also be readily harnessed by brands driven by short-term demands such as movies and music.
10. Engineer 360⁰ media communications. Custom-constructed, cross-platform activities provide opportunities to break through the morass of more standard media offerings.

Of all media-related opportunities outlined above, the last two can be especially powerful. In particular, UM has seen word of mouth trust levels double those for TV advertising. Moreover, our detailed custom research programs reveal that customized media solutions can often help boost ROI by +600%.

So where will Always-On take us next? Paradoxically, social TV, i.e. commenting on TV programs in real or near-real time via social media, also appears to be driving the totally unexpected revival of live TV! According to a study by TVGuide.com among its panel of 10,000 consumers, the number of people claiming to watch live TV in order to avoid social media spoilers has grown from 20% to 27% in the last two years. It’s an ironic twist of fate that the internet appears to be helping to rebuild TV, the very media channel it has competed with for viewers over the last ten years.

Intrigued by this phenomenon, we sought some insights from UM’s panel of preselected, academic psychologists about “Always On.” These psychologists come mainly from U.S. universities and similar institutions, and are typically leading professors and thinkers in their field. The panel pointed to academic findings that emerged last year – the culprit is dopamine.

In responding to calls, emails, texts, social media, etc., our electronic devices play to a primitive impulse to react to immediate threats and dangers. Our responding to that call, email or social media post provokes excitement and stimulates the release of dopamine to the brain. Little by little, we become addicted to its small kick in regular, minute doses. In its absence, people feel bored.

Dopamine is a hormone, a neurotransmitter, associated with the pleasure system of the brain. It reinforces certain activities and habits, which in turn creates habituation. Drugs such as cocaine, nicotine and crystal meth induce exceptionally large releases of dopamine, which is a testament to the addictive powers of the hormone.

This led us to ask the burning question: Is being “Always On” bad for us? To this, the panel of psychologists cited Sigmund Freud’s book, Civilization and Its Discontents, where Freud contends that since the dawn of man every technological advance has been met with a level of resistance and skepticism. For example, the ancient Greek scholar, Socrates, riled against the idea of writing because he argued it could destroy our motivation and need to memorize.

Nevertheless, “Always On” does cause unwanted modern-day anxieties. For example:

• It creates loss aversion when we are deprived of access to our smartphone.
• There is the stress of connecting with friends via social networks which is especially true for younger individuals where it may fire up:
• Jealously, e.g. a teenage girl’s boyfriend may “friend” another girl she doesn’t like, or
• Ostracism, e.g. a teen boy may see his friends organizing an event where he’s inadvertently not invited.
• Sexting, where even senior public figures who really should know better get caught.

We then probed further: is “Always On” bad for brands? Intriguingly, the psychologists on the panel said that the distractions created by “Always On” should not have to adversely impact strong brands. “Always On” increases on the simplicity for (younger) consumers to compare brands, making the best decision with regard to price, features, etc. They elaborated further and explained that “sticking with one good brand is cognitively easier than switching from brand to brand.”

Equally, mediocre brands and bland marketing communications may flounder in the new media ecology. Brand loyalty takes on a completely new perspective for many brands: “It’s less about driving customer loyalty to a brand and more about a brand being loyal to customer.” How many brands can rise to the marketing challenge of proving to consumers they are in it for the long-haul?

For brand communication, it’s about ensuring decision making is easy, pleasurable and emotionally rewarding. By emotionally rewarding, we mean it is essential to follow the most fundamental messaging ethos: “Don’t sell the steak, sell the sizzle!” Or as Harvard Professor Theodore Levitt famously noted, “People don’t want quarter inch drills, they want quarter inch holes.”

So “Always On” doesn’t have to be a quagmire for brand communications, but brand managers do need a powerful internal gyroscope to ensure a brand’s enduring qualities are clearly visible to uphold the brand’s abilities and to exceed consumer expectations over the savageries of time.

Let’s assume for one moment that we have a great ad, a creative asset that resonates well with the consumer. Is that enough? Our initial regression modeling suggests that besides a great ad, just maximizing the audience rating may not be enough. Critically, the quarter of the game that the ad appears in and securing the first position in the pod also count. In addition, :5 billboards, those announcements often seen at the beginning or end of an ad pod, may be an unnecessary luxury and, from the perspective of WOM value, possibly not worth the additional investment.

In 2010, UM won the Word of Mouth Marketing Association’s (WOMMY) Gold Award for Research for its paper quantifying how Sony Electronics’ media advertising helped boost its word of mouth. Through a multivariate analysis, we determined two key insights that had never been publicly demonstrated before:

1. Brand advertising has a direct effect on the effectiveness of word of mouth. In this instance, 14% of all Sony Electronics’ WOM was attributable to its own media activity.

2. A brand’s word of mouth is not just affected by its own ad activity. Competitive share of voice is also a critical factor. In the Sony Electronics model, 23% of Sony’s potential WOM was eroded by the impact of competitors’ advertising activity.

If we apply this type of modeling approach to ads in the Super Bowl, what can it reveal? To determine this, we analyzed the reported word of mouth from Keller Fay’s Talk Track Super Bowl study conducted in 2011. Keller Fay takes a unique approach in the world of buzz trackers in that it captures both online and offline word of mouth. Keller Fay was the data source fuelling the award winning WOMMY study. For the Super Bowl, Keller Fay specifically tracked 42 ads in the game with sample of 3000 individuals boosted during the week after the game with a custom survey.

It is well-known that word of mouth levels vary substantially by market category. Additionally, since several advertisers had multiple placements and various commercial time-lengths in the Super Bowl, we decided to focus on one category where these variables would be minimized. We chose to probe the movie sector since not only did this eliminate any cross-category effects, we were able to substantially reduce the variations from ad to ad. For example, there was only one ad for each film title and 30 seconds was the only commercial time-length utilized by all movie marketers. This enabled us to isolate the core media drivers of movie mentions as a direct result of their Super Bowl advertising.

To analyze the effects of the Super Bowl, we built a database of factors such as 18-54 TV rating, the game quarter in which the ad appeared, ad position in pod, use of billboards plus the word of mouth for each movie in the week after the Super Bowl that we applied to each ad. Interrogating this database via regression analysis, this is what the model revealed:

The model’s projection is very encouraging with a 99% fit between predicted and actual word of mouth. While one core factor was audience rating, it was also bolstered by the quarter in which the ad appeared – the earlier the better. We also saw that being first in pod provided great impetus to an ad’s WOM. By contrast, the often highly prized position of last in pod did not materially help WOM; indeed it actually reduced the ad’s effectiveness!

The jury remains out on billboards. In our best model, displayed in this column, billboards did not help word of mouth reach, i.e. the net number of people discussing the ad, but in other models, the gross volume or frequency of conversations were helped by billboards.

For UM, the surprising reveal of this analysis is the low value of word of mouth derived from being placed last in pod – a media position which, otherwise, can often be highly regarded. We hope to build and share on this analysis in future years. 2012 should be another great year for Super Bowl advertising and its legend ability to motivate consumers to talk about brands.

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.