Three-quarters of our business comes from stuff that Don Draper wouldn’t have recognized 30 years ago. We probably wouldn’t have recognized it ourselves 15 years ago.

Sir Martin Sorrell, Founder, WPP

There’s no need for a long drawn out description of the history of commercial media. All you need to know is that until the noughties, media evolved steadily and in line with technology, from town crier to the Gutenberg Press to radio to television to direct response to cable to the internet. And the past 15 years have offered some moments in time that represent critical change to the fate of our industry. A period that has brought chaos to the CMO like no other time in marketing. A period where brands have been made and broken. Not even Don Draper could have foreseen this level of change, nor could he have recommended how marketers should respond. He was a simple ad guy in a simple time.

1.1 Critical Media Moments in Time

1.1.1 Blitzscaling and the Accidental Media Companies

It took television 30 years to go from black and white to colour, yet in a little over five years Mark Zuckerberg took a website called FaceMash to one of the biggest media brands in history. Within six years of launch it was amassing 400 million people a month. Welcome to ‘blitzscaling’. A concept coined by Reid Hoffman (co-founder LinkedIn) around the idea of how companies attain explosive growth, lightning fast. It is about doing and building things others won’t, and thinking unconventionally about rules, risk and pivoting. It is a 10% growth per day thing, not 10% growth per year (which is better than most marketers could dream).

Hoffman cautions that the approach is not for the light-hearted. Not everyone has the stomach for this type of thinking. In a high-stakes winner-takes-all game, losing foretells of biblical proportions. Netscape were perhaps one of the earliest examples of blitzscaling, rising to an eye watering US$2 billion market cap in 16 months, but they are also an example of falling hard. Within ten years of its establishment the browser service went from 90% market share to less than 1% in 2006. Regardless, Netscape made its mark on the world.

In the noughties several websites out of the pioneering Silicon Valley went from zero customers to a gazillion in record time. And the value of these customers’ eyeballs was quickly realised. Creating a commercial online media platform became the new business model, even when the original plan may not have been. Zuckerberg famously held back on commercialising advertising until four years after the business began. His initial focus, he claims, was more on connecting everyone in the world and less about the advertising opportunity. He talked about taking on advertising to pay the bills. Sheryl Sandberg, in 2008, saw advertising for the opportunity it was. YouTube, in its youth, was an innocent place dedicated to a small group of creators motivated by their art. In 2006, less than 12 months later, it was sold to Google and advertising monetisation began two years after its launch. It’s hard to believe, but in the early days Google was opposed to advertising-supported search engines due to the bias it may bestow. Amazon started as an online trader, with a slower evolution to becoming an ad seller. Now it is fast on its way to becoming one of the biggest media companies in the world. None of these company’s missions have changed, but the definition of what constitutes a customer sure has. They are in the business of attracting the attention of customers and re-selling it.

In less than five years the marketplace was filled with gargantuan advertising opportunities on social, search, video and microblogging. This was the first time in history marketers could easily access global reach in one place; providing an answer to the fragmentation problem of the eighties and nineties. Consequently, over a few short years the shift in advertising spending away from traditional platforms to new media was about as epic as blitzscaling itself.

Not surprisingly, the scale of this disruption has had its consequences on the broader industry. Fundamental shifts are never easy. In 2018, complaints were made to the Australian Competition and Consumer Commission (ACCC) arguing that the digital duopoly (Facebook and YouTube) were ‘rule bending’ and should be more closely scrutinised by regulators (as the traditional platforms have been). This included complaints regarding the facilitation of content piracy, lack of transparency for measurement, and data aggregation. These are weighty complaints. The piracy claims were based on platforms not providing any financial contribution towards TV content being viewed on social sites. Data aggregation becomes a problem when critical mass restricts new entrants into the marketplace. But perhaps the most talked about issue in advertising circles is measurement transparency. A lack of transparency over the algorithms, makes it difficult for competition regulators around the world to assess anti-competitive conduct. Since then a USA congressional inquisition expressed concern for privacy and monopolisation from Facebook, while EU countries have launched legal challenges on Google and Facebook for privacy and anti-trust practices.

The point here is to demonstrate that rule bending is a classic blitzscale technique without which these companies wouldn’t exist. And this rule bending has literally changed everything about media and advertising (and life as we know it more generally). We have information organisers, video sharers, social and professional networkers, auctioneers and news gatherers all now sitting safely in the media owner category (although for regulatory purposes, some refute that they are). This is a category that has been dominated by a select few for many decades.

QUICK EXPLAINER

The ACCC Digital Platforms Inquiry

The Australian Competition and Consumer Commission (ACCC) is an independent Commonwealth statutory authority whose role is to enforce the Competition and Consumer Act 2010. As well as a range of additional legislation, promoting competition, fair trading and regulating national infrastructure for the benefit of all Australians.

On 4 December 2017, the then Treasurer, the Hon Scott Morrison MP, directed the ACCC to conduct an inquiry into digital platforms. The inquiry looked at the effect that digital search engines, social media platforms and other digital content aggregation platforms have on competition in media and advertising services markets. In particular, the inquiry looked at the impact of digital platforms on the supply of news and journalistic content, and the implications of this for media content creators, advertisers and consumers.

The final report was published on 26 July 2019.

The ACCC suggested that the dominance of the leading digital platforms and their impact across Australia’s economy, media and society must be addressed with significant, holistic reform.

The wide-reaching report contains 23 recommendations, spanning competition law (the ability for other media businesses to compete), consumer protection and privacy law (control over usage and collection of personal data) and media regulation (disinformation and a rising mistrust of news).

As at October 2019, the Australian government was considering all recommendations.

See the final report here: https://www.accc.gov.au/publications/digital-platforms-inquiry-final-report.

1.1.2 Free Reach and Going Viral

The next critical media moment in time involves kittens and babies. You’ve heard it before. Put a cute baby in a video and it will go viral. Kittens on roller skates will spread video content wildly from a small base on the internet through social and email. Unfortunately, the term viral is one of the most grossly misused marketing words today. The term was catapulted by the meteoric rise of YouTube after Google bought the company in 2006. Unlike watching traditional video on TV, users were encouraged to engage in the content by way of commenting, rating, favouriting and, of course, sharing to other users. Now, going viral carries its own identity beyond YouTube and is used for just about any content sharing on any media site—word-of-mouth on steroids.

As a medical term, viral has been used for at least 300 years, most often during an epidemic to describe the spread of a virus from a single host to many people. Like many marketing terms borrowed from other sectors, viral is loosely understood and even more loosely measured. The concept of going viral is a function of time and the rate of sharing—the rate of sharing means the ratio between number of views to number of shares. For a video to be truly viral, this ratio needs to present as views < shares. In layman’s terms, one person views the video which results in many more people sharing. As such, the concept of viral has borne the impression that online video advertising will bring you free reach—that if we build it (and upload it) they will come in droves without additional cost (or the need to invest in reach at all).

As word-of-mouth on steroids, the viral concept is flawed by the natural shape of content distribution (a reverse J-shape curve). The reality is, and our own extensive work has proven, that the likelihood of a video spreading to millions from a small seed is highly unlikely, and upfront paid seeding plays a bigger role than most people think. Nevertheless, going viral has catapulted us into the world of earned media where marketers are seduced by the free eyeballs lottery. This is the critical media moment in time that turned marketers into gamblers, and like real gamblers they ignore the fact that the odds are stacked against them.

REMEMBER THIS SIMPLE TRUTH

The concept of viral marketing is utterly flawed by the nature of the shape of the sharing distribution.

1.1.3 Instant Measurement Appeared in an Instant

The first rule of social software design is that more engagement is better, and that the way you get engagement is by adding stuff like Like buttons and notifications.

James Somers, Contributing Editor, The Atlantic Boston

In the mid-noughties, Justin Rosenstein delivered a masterstroke for Facebook, co-inventing the Like button and single-handedly changing the nature of how we consider advertising success. While other metrics (such as, views, shares, comments, ratings) had been introduced on YouTube a few years earlier, the Facebook Like button was the first time customer approval was directly linked to a brand (as opposed to content) at such scale. In the early days Like was literally taken as being a fan of the brand. In my own research at the time we debunked this myth showing that in an average week less than 1% of the brand fans bothered to return to the page they had Liked. Since then, Liking has become more widespread along with its other engagement cousins—followers, visitors, viewing minutes, reactions, retweets, favourites, watch list, mentions, dislikes, clicks, shares, views, comments and the list goes on (and on). These are all favourite online volume metrics used to measure the success of online campaigns.

But there are no unicorns and glitter in Fight Club. And two highly significant (negative) flow-on effects resulted from the adoption of instant measurement.

First, the rise of short-termism. With easy access, marketers have become addicted to instant measurement (no real surprises there). What this means is that they have switched focus from investing in and measuring, longer term brand impacts. The new focus has prompted fleeting campaigns that see immediate spikes in sales and have easily accessible ROI metrics. Traditional advertising research takes time for a number of reasons, including (but not limited to) the need for complicated experimental and sample controls. Lack of measurement controls means that online engagement metrics are often skewed by market share giving an uneven representation of buyer distribution. For example, big brands have more buyers, so engagement volume from a bigger brand might look acceptable on the surface, but in reality the brand could be underperforming for its size. Actual volume doesn’t tell the whole story. Heavy buyers typically respond to short-term campaigns and are more likely to engage in liking/sharing/commenting in brand communities. Engagement from these customers is expected and tells us nothing about brand growth potential.

Secondly, our obsession with and willingness to pay for instant measurement has impelled the ugly world of ad fraud at eye-watering scale (more on this in Chapter 8). There are two common types of ad fraud—impression fraud and click fraud. Instant measurement has given the green light to both. Thanks to advertisers’ obsession with short-term metrics, a whole underground (illegal) market has emerged to falsify their volume.

Instant measurement provides no good outcome for the advertiser. Either they pay for fake engagement or, perhaps worse, the metrics they rely on for campaign effectiveness have no rigorous base. History has taught us that sometimes the flow-on effects from a discovery are far more powerful and pervasive than the original event. When nuclear fission was discovered in 1938 by Otto Hahn and Fritz Strassmann, they couldn’t have imagined where it would end up. It took until 1952 for the Americans to test their first nuclear weapon. Now in 2019, nine countries have over 15,000 nuclear weapons. While not nuclear, the scale of instant measurement is massive and its flow-on effects bestow a far greater critical moment in media than its initial development.

1.1.4 The Machines Arrived

In the midst of the blitzscaling boom media buying automation arrived, and the purchase of Double Click by Google ignited an era of programmatic trading. Suddenly the manual processing of buying media was taken away from humans and given to much smarter computers to automate which ads to buy and how much to pay for them (more in Chapter 4). Programmatic started as a way of using up remnant digital inventory but it has evolved to become the very soul of real-time online targeting. Real-time online targeting means advertisers can now access target customers anywhere in the world in the very instant they display online buying cues. It is opportunistic and it capitalises on intent (or signals thereof). It reportedly offers marketers the opportunity to accurately apply the principles of recency (see Chapter 8).

In theory this is gold. In reality, it encouraged brands away from marketing to many people, to mining for fewer people in a hyper-relevant way. This added more fuel to the damaging obsession with instant everything and short-term thinking. While Google pioneered the targeted advertising business model in the late 1990s, Sheryl Sandberg didn’t introduce it to Facebook until 2008.

As if by sliding doors, Jon Mandel broke the ad agency model in the mid-2000s. Jon Mandel was a heavy hitting agency CEO who lifted the lid on agency rebates, kickbacks and all things transparency and trust. What followed from his whistleblowing speech was nothing short of a category 5 hurricane. Firstly, approximately US$50 billion of accounts were put up for review, then a second wave of disintermediation is said to have occurred when advertisers started going direct to online publishers. The online publishers readily embraced this by ramping up operations to focus on direct relationships with advertisers (and their data). It was perfect timing for the growth and commercialisation of online targeting. As a consequence, Google and Facebook are now said to bank some of the richest first and second party data in the world.

And bang, this is a super critical moment in media history. The assignment of power to a few main players in digital. Those who own the data, own the world.

QUICK EXPLAINER

Trying harder as the underdog

‘We Try Harder’ was a famous Avis car rental print campaign in the 1960s and 1970s that changed their fortune. The campaign debuted in 1962 when Avis was dominated by the number one in the market, Hertz, and at a time when Avis was not turning profit. Doyle Dane Bernbach (now known as DDB) was employed to help. Knowing Hertz was light years away in terms of market share, the objective of the campaign was to embrace their second-place position to turn the business around. Bill Bernbach, the co-founder of DDB, asked management why anyone ever rents a car from them. Their response, ‘because we try harder’, then became a promise to their consumers about the quality of service. The famous tag line was born and it elevated the brand’s status to the point that in one year the company went from losing US$3.2 million to turning a profit of US$1.2 million for the first time in 13 years.

In 2012, after nearly 50 years, Avis dropped the distinctive tag line for something that promises consumers nothing and is much less memorable, ‘It’s Your Space’. That CMO has come and gone.

1.1.5 Hyper-Personalisation (aka Web of One)

When Facebook or Google point their supercomputers toward our minds, it’s checkmate.

Tristan Harris, Founder, Center for Humane Technology

There is a painfully awkward conversation between Dr. Evil and Frau in Austin Powers: The Spy Who Shagged Me (1999, New Line Cinema) after their one-time sexual encounter, where Dr. Evil states the obvious to Frau, ‘It got weird didn’t it?’. Well perhaps the next critical media moment in time can be explained in the same way—it got weird.

From a place of good intention, real-time targeting went from technology that could find groups of target customers for the purpose of marketing efficiency, to hyper-personalisation algorithms that monitor you on and offline 24/7. Your phone, IoT devices, and smart TV know every single thing about you and your friends, for the sole purpose of predicting your next move. All in the name of marketing efficiency.

Surveillance capitalism becomes the tool for hyper-personalisation.

Professor Shoshana Zuboff, a subject matter expert on surveillance capitalism, talks about the level of monitoring online being akin to criminal. She says, ‘Most Americans realize that there are two groups of people who are monitored regularly as they move about the country. The first group is monitored involuntarily by a court order requiring that a tracking device be attached to their ankle. The second group includes everyone else…Just like 20th century firms like General Motors and Ford invented mass production and managerial capitalism, Google and Facebook figured out how to commodify ‘reality’ itself by tracking what people (and not just their users) do online (and increasingly offline too), making predictions about what they might do in the future, devising ways to influence behaviour from shopping to voting, and selling that power to whoever is willing to pay.’

But our conversation is not about the legal, ethical, social, political rights and wrongs of surveillance capitalism. There are plenty of ex-Google/Facebook/Mozilla employees happy to talk and write about that—Ken Auletta, Roger McNamee, James Williams, Tristan Harris, Aza Raskin. This conversation is about what it might mean for brands.

Let’s start with the The Filter Bubble. Even back in 2011, Eli Pariser, a political and internet activist, started talking about invisible algorithmic editing and information control. He is less finger pointing than some other activists. He talks more broadly about how filter bubbles are formed, often with a skewed look of life, when an algorithm chooses what you see and what you don’t see.

He argues that before the internet we were controlled by editors of news who decided what we saw/read/heard and what we didn’t. Then along came the internet and we all felt liberated but, he argues, we are not. There is a passing of the control torch from human editors to algorithmic editors. And filter bubbles are formed, Pariser describes, when we don’t see a balance of Homelessness AND The Oscars, the war in Afghanistan AND Justin Bieber, people like you AND different people. More recent activists in this space speak of the same bubbles, acknowledging that bubbles are a pre-disposition in someone’s mind and the nature of the algorithm (at times wrongly) confirms the idea.

It’s easy for things to get weird when your social reference points are removed or manipulated (that’s how a cult works). That’s why Frau loves Dr. Evil, yet he is actually evil and wants to rule the world. But filter bubbles are good for the commoditisation of attention. The online platforms want Frau to love Dr. Evil, and they don’t want to show her content that makes her think otherwise.

Hyper-personalisation is still in its (relative) infancy and its first real game-changing application is the new retail model (Amazon model). Real-time personalisation engines within an e-commerce platform move us from actively seeking out/shopping to functional buying. These algorithms narrow down our choices making decisions based on previous first choice and wants. It weeds out the ‘purported’ clutter. When this happens two things disappear: curation of information and the importance of needs over wants. Is this where we are headed with all hyper-personalisation marketing? How do brands navigate this new model? Does traditional marketing, and repertoire buying, fit in? Do they simply need to nail product quality, physical distribution and customer user experience?

That takes us back to a 1950s scenario. You drive a Chevrolet. The dealer is in your local town, he knows what you need and want. He can deliver it to you. But of course, in those days, if you had a falling out with the Chevrolet dealer you drove to the next town and went to their dealer. Now, there is no next town. So, are function and distribution the new norm? Where distribution means tactical negotiation with algorithm owners and this becomes the new shelf space planning?

When you look under the hood of the Amazon search engine ranking algorithm (as much as the public can) there are a number of things that challenge the current advertising charter .

Their number one end-goal is degree of sales conversion over time, which is not overly surprising, but they reward brands (with ranking) that achieve more of this. This means those who achieve greater sales velocity relative to their competition for the same search term win the higher ranking (i.e. recent [weighted] vs. lifetime sales velocity). Those who gain higher ranking also close the loop on the bubbles. It becomes self-fulfilling: big brands have more customers who buy more often. Without even trying, big brands win. So, what does this model do for the future of small brands? Will small brands die and big brands get bigger? Or perhaps big brands won’t get bigger because user relevancy plays a role in the search term, so we would expect that sales on this site will come more from heavier buyers than from light buyers. Also, Amazon rewards brands (with higher ranking) who advertise within their ecosystem. Again, not so surprising. Not only does this foster big brands again (because they have more money to advertise), but it also challenges the nature of creative and branded content as we know it. They make it very clear you are creating ads for the machine first, human second .

So many questions, not many answers. And here are some more.

If humans are noted to be impacted by the skew of the editorial, will some brands naturally never earn exposure? Will competition law, consumer protection and privacy law force a day of reckoning? Will there be an AdTech crash?

And the big one, will laws of brand growth hold? More on this in Chapter 2.

The only thing we know for sure is that no-one knows the answers. We need future-facing research agendas that help us navigate all these questions. We don’t need filtered information from those who stand to make the most commercially from their answers. Plus, we do know for sure that targeting got weird.

Make sure you read Chapter 9 for a considered glimpse into the future.

1.2 What Have These Critical Moments Done to the Advertising Troops?

1.2.1 Factfulness and Confusion

Over the past 15 years everything has changed about advertising and media, or has it? Is it possible that the marketing we practised before the blitzscaling period doesn’t apply?

Do we have a grasp of both sides? Unlikely. Could we be living in a bubble? Most likely.

A book I whole-heartedly recommend is called Factfulness: Ten Reasons We’re Wrong About the World and Why Things Are Better Than You Think. The author is Hans Rosling, a Harvard Humanitarian Award winning medical doctor, Professor of International Health, and one of Time Magazine’s 100 most influential people in the world. The book was his last-ditch effort to fight global ignorance and calm fears before he died in 2017. It is about perception versus reality, fact versus opinion, generally how humans live in a bubble of mega misconception about how the world really works. Remarkably, it was written before the time when curation of information was controlled by algorithmic editors.

Professor Rosling’s major thesis is that as humans we overdramatise stories resulting in the very large majority of us (around 86%) interpreting the world devastatingly and systematically wrong. Like the way we (some of us) feel the 1970s was a much better time to grow up. But in reality, when we consider the facts around increased access to education, reduced deaths from cancer, greater rate of democracy etc., it wasn’t. He calls the concept Factfulness versus Fact-based. Rosling suggests there are a few reasons why humans are Factful. One being our tendency to think in a binary way when a vast gap exists between extremes. Or, our lack of capacity to process large amounts of information so that only the dramatic shouty headlines get past our attention filter. Perhaps the reason most relevant to the marketing industry is the concept of the view from up here. A concept where people on the upper level of society honestly have no concept of how the other side live. While Rosling was talking specifically about the rich and poor, the analogy can be applied to any divided population where those in a bubble might think they understand those outside the bubble. When really they don’t.

Advertisers operate in a state of Factfulness, where opinion is rife over facts. There are studies that show bubble thinking in the context of audience consumption. Three separate large-scale studies run in 2016 (UK) and 2017 (Australia, Canada), considered how advertising professionals (AdLand) perceive the media consumption habits of normal people, then cross compared to the reality, based on actual data. The AdLand sample comprised advertisers, media agencies, creative agencies and media owners. The findings were strikingly similar for each country. It would seem the inhabitants of AdLand grossly overestimate the online media consumption of normal people (consumption of Facebook, YouTube, Twitter, Snapchat, Instagram), while these same people significantly underestimated time spent viewing on TV.

It’s not about which platform wins a prize. The point is that when one group lives in a vastly different manner to another, a bubble appears and perceptions of the other half can be wrong. Facebook and YouTube, in particular, are exceptional and consistent purveyors of their own value (TV not so much). They run programs where staff are placed within advertising agencies for the direct purpose of teaching advertisers how to advertise on their platforms. It’s not surprising perceptions of those in AdLand are out of whack.

Next, Wiemer Snijders presents bubble thinking in the context of brand growth.

1.2.2 Confusion is Driving us to the Right (Not Left) Side of the Banana

By Wiemer Snijders

Being out of touch with consumers is one thing, and of course it’s not ideal if it’s your job to sell to them, but marketers also seem out of touch with themselves.

Since 2008, twice a year a large group of Chief Marketing Officers (CMOs) is asked about their outlook on a broad range of topics in what is called the CMO Survey. It is sponsored by prominent companies such as Deloitte, the American Marketing Association, and the Fuqua School of Business. It is widely promoted in trade publications as a guide on what to expect in our crazy marketing world. But how much value should we place on what marketers think? Do these predictions come true? Casting our gaze back to some previous predictions can prove interesting. For example, in 2014 the survey results predicted that expected spending on social media would rise to 25% of their total budget in five years. Yet in 2019 spending on social media remained at a stable 10%.

Expectations (and predictions) often fall very short of reality. To be honest this is similar to the gap between consumers and intention, expectation and reality can be polar opposites. Marketers aren’t the only people who have a hard time predicting the future, but they also struggle to reconcile the usefulness of intent as a metric.

The idea that consumers are becoming more fickle or unpredictable, is arguably one of the most frequently used predictions in reports like the CMO Survey. To date this is not supported by facts. By contrast, Jeff Bezos, Amazon’s founder and CEO, once mentioned that he was more interested in the things that would not change in the near future, as these were the things he would be able to build his business on. This is a universal truth underpinning investment, so I wonder why marketers don’t look at non-change in this way. Instead, they often ignore the things that are stable and can be truly predicted. Bill Bernbach (of DDB fame) introduced the notion of the ‘changing man’. But concentrating efforts on the changing man has led to an even more pronounced focus on the short-term use of metrics.

So, everything is different now, right? Not so. Sixty years of scientific research has consistently found that people’s buying behaviour follows a very robust pattern. Over that time, not much has changed when it comes to buying. One of marketing’s most fundamental findings is that every brand’s customer base looks like a banana (technically, reverse J-shape distribution). Although he left the fruit out of his description, it was Andrew Ehrenberg who first described the distribution of a brand’s buyers as a Negative Binomial Distribution (NBD). As you can see in the illustration, most buyers are on the left of the curve. These people will have only bought the brand once or, at most, just a few times during the time period measured. This is arguably the most important insight: a lot of people buy a little, and a few do buy a lot (but there are fewer of them). It is because of this distribution (and the statistical patterns that sit below it) that brand growth depends on adding more buyers and these already large groups of (very) light buyers buying even once more. Rather than attempting to increase loyalty of the already heavy buyers. Think about relative expandability.

This model of distribution (technically called the NBD-Dirichlet model of buyer distribution) shows that collectively, people’s propensities to buy will not vary much. It is a reliable, descriptive and predictive model of consumer buying behaviour. So remember this, all brands follow the reverse J-curve, with few people buying a lot and a lot of people buying a little (Fig. 1.1).

Fig. 1.1
figure 1

The NBD and the banana

Full size image

Bringing this back to how the marketing troops are currently faring, the nature of change in the media landscape means that marketers are often swimming against the current of science. Data and technology have only exacerbated this, and they find themselves focusing on what is more immediately and easily measurable.

Evidence of being on the wrong side of the banana is perhaps most famously connected to Peter Field and Les Binet. Their work on the IPA Effectiveness Awards Databank which contains results from thousands of campaigns from 1998 to 2016, shows that overall campaign effectiveness is declining. This is because companies who focus on activation and short-term objectives are targeting heavy buyers (or at least not fishing for light buyers as well). Targeting technology is set up for this. It tends to look for those who have bought before, and more rarely for those who haven’t or who buy infrequently. Mostly because the infrequent buyers are harder to see. Activation campaigns aimed at existing buyers will give you instant rewards because they were likely to buy anyway, but not because the campaign was more effective. How many evaluations deduct normal sales without the campaign? Instant results like clicks and Likes mean instantly happy CMOs and CEOs. Peter Field rightly compares these activation campaigns to fireworks: a short-lived spectacle with little residue .

To me the notion of focusing on the changing man is like an industry driving backwards. I grew up in the Netherlands. In the 1980s a Dutch television show hosted backwards driving competitions on race circuits. Roughly translated, it was called Racing in Reverse. Some say that Dutch reverse racing is the funniest thing they have ever seen. Reverse gear is there for a reason in vehicles and is used only occasionally. If we want to move forward, we tend to use the other gears. Businesses aiming to grow, need to choose the forward gears and focus on lighter and non-buyers on the left-hand end of the banana. Even though we need to continue to encourage heavier buyers, focusing all of our efforts on the right-hand end of the banana is like driving in reverse.

1.2.3 The Wrap up

If you haven’t noticed the degree of change in our world over the past 15–20 years, perhaps you have been living underground. While change is normal and healthy, learning how to navigate this new thing called cable TV after years of linear TV is in no way comparable to navigating this new thing called surveillance capitalism after years where our privacy and our data was largely protected. So at the risk of sounding cliché, the rate of disruption in our industry, and for the poor unsuspecting consumer, is like no other time in history. And this is not from a place of Factfulness, rather from a place of fact. This book aims to help marketers and advertisers shift into forward gear given the current state of play and act as an eye-opener in readiness for the future state of marketing.

MEANWHILE IN THE REAL WORLD

Scott Galloway the Prophet

One of the most revered, and certainly feared, commentators in our industry is Clinical Professor Scott Galloway (NYU Stern School of Business). He is revered because of his numerous high-profile board positions including Eddie Bauer, The New York Times Company, Gateway Computer (acquired by Acer) and others. Because he has founded and grown many companies, including: Prophet (a brand strategy firm), Red Envelope (a multichannel retailer that went public in 2002), and L2 (a subscription research and business intelligence firm that benchmarks the social, search, mobile, and site performance of the world’s largest consumer and retail brands). L2 was acquired by Gartner for US$134 million in 2017.

But it’s his no-holds-barred, no-mercy style commentary that makes him one of the most feared. Particularly by those he calls the Four Horseman: Amazon, Apple, Facebook and Google. In 2017, he discussed the ‘hidden’ DNA of these companies, talking about how Apple mimics religion with its own belief system, objects of veneration, cult following, and Christ figure. And how a disturbing aspect of today’s media duopoly, Facebook and Google, is their abdication from being called media at all, which seems to absolve them of all social responsibility.

The public gut punches continue each week in his No Mercy/No Malice blog where he shares his take on tech and relationships in the digital economy. Titles like ‘Billionaires Behaving Badly’, ‘Facebook 1, Congress 0’, ‘From Russia with Likes’, ‘Alexa, how can we kill brands?’ and ‘WeWTF’ are sure to conjure fear from those he targets. Part of his blog includes his highly anticipated annual predictions on the happenings in the media and tech industry for the following year. Clearly, some are designed to get your attention, like the prediction that Sheryl Sandberg and MacKenzie Bezos will marry in 2019, but most are serious and based on his research. Looking back over the years Galloway gets his predictions right only about half of the time, but when he does get it right the tectonic plates of our marketplace shift just a little bit. He makes big calls about big industry players, here are a few that he got right:

  • Slack will take over email for internal communications in 2016

  • Netflix will become the operating system for television in 2017

  • Cryptocurrency will crash in 2018

  • Big tech firms will start to see bigger fines and tighter data protection laws in the EU and more hearings in the US in 2018

  • Amazon to surpass Apple in value in 2018

  • Voice (specifically Amazon’s Alexa) is going to be the next big thing in 2018

  • Walmart will become the online grocery leader in 2019

  • weWork will not IPO in 2019 (well, they tried).

If his 2020 predictions are right, by 2020 Uber will lose 80% of its value, 30% of all searches will be ‘queryless’ as visual search becomes dominant and Amazon will be in the healthcare business. I’m not sure how I feel about an appointment with Dr. Amazon, we will have to wait and see.