Category Archives: The New Marketplace

Watson:2020 – America’s Self-Driving Presidency

Ken Jennings, the second most successful Jeopardy player of all time, has an IQ of 175. That makes him smarter than 99.9998615605% of everybody. If you put him in a city the size of Indianapolis, he’d probably be the smartest person there. In fact, in all of the US, statistics say there are only 443 people that would be smarter than Mr. Jennings.

And one machine. Let’s not forget IBM’s Watson whupped Jennings’ ass over two days, piling up $77,147 in winnings to Jennings $24,000. It wasn’t even close. Watson won by a factor of more than 3 to 1.

That’s why I think Watson should run for president in 2020. Bear with me.

Donald Trump’s IQ is probably in the 119 range (not 156 as he boasts – but then he also boasted that every woman who ever appeared on the Apprentice flirted with him). Of course we’ll never know. Like his tax returns, any actual evidence of his intelligence is unavailable. But let’s go with 119. That makes him smarter than 88.24% of the population, which isn’t bad, but it also isn’t great. According to Wikipedia, if that IQ estimate were correct, he would be the second dumbest president in history, slightly ahead of Gerald Ford. Here’s another way to think about it. If you were standing at a moderately busy bus stop, chances are somebody else waiting with you would be smarter than the President Elect of the United States.

Watson won Jeopardy in 2011. Since then, he’s become smarter, becoming an expert in health, law, real estate, finance, weather – even cooking. And when I say expert, I mean Watson knows more about those things than anyone alive.

Donald Trump, on the other hand, has probably learned little in the last 5 years because, apparently, he doesn’t have time to read. But that’s okay, because he reaches the right decisions

“with very little knowledge other than the knowledge I [already] had, plus the words ‘common sense,’ because I have a lot of common sense and I have a lot of business ability.”

In the President Elect’s mind, that also qualifies him to “wing it” with things like international relations, security risks, emerging world events, domestic crises and the other stuff on his daily to-do list. He has also decided that he doesn’t need his regular intelligence briefing, reiterating:

“You know, I’m, like, a smart person. I don’t have to be told the same thing in the same words every single day for the next eight years. Could be eight years — but eight years. I don’t need that.”

That’s right, the future leader of the free world is, “you know, like, a smart person.”

Now, President Watson could also decide to skip the briefing, but that’s because Watson can process 500 gigabytes – the equivalent of a million books – per second. Any analyst or advisor would be hard pressed to keep up.

Let’s talk about technology. Donald Trump doesn’t appear to know how to use a computer. His technical prowess seems to begin and end with midnight use of Twitter. To be fair, Hillary Clinton was also bamboozled by technology, as one errant email server showed all too clearly. But Watson is technology: and if you can follow this description from Wikipedia, apparently pretty impressive technology: “a cluster of ninety IBM Power 750 servers, each of which uses a 3.5 GHz POWER7 eight-core processor, with four threads per core. In total, the system has 2,880 POWER7 processor threads and 16 terabytes of RAM.”

In a presidential debate, or, for that matter, a tweet, Watson can simultaneously retrieve from its onboard 16-terabyte memory, process, formulate and fact check. Presumably, unlike Trump, Watson could remember whether or not he said global warming was a hoax, how long ISIS has actually been around and whether he in fact had the world’s greatest memory. At the very least, Watson would know how to spell “unprecedented”

But let’s get down to the real question, whose digit do you want on the button: Trump’s “long and beautiful” fingers or Watson’s bionic thumb? Watson – who can instantly and rationally process terabytes of information to determine optimum alternatives – or Trump – who’s philosophy is that “it really doesn’t matter…as long as you’ve got a young and beautiful piece of *ss.”

I know what you’re thinking – this is us finally surrendering to the machines. But at least it’s intelligence – even if it is artificial.

Note: In writing what I thought was satire, I found once again that fact is stranger than fiction. Somebody already thought of this 4 years ago: http://watson2016.com/

The Cathedral and Bazaar Cycle of Mar -Tech Innovation

Each year my friend Scott Brinker sits down to update his marketing technology landscape and each year he is amazed by the explosion of vendors he has to fit on a single slide. Last year’s version clocked in at 3874 Mar Tech solutions – almost twice as many as 2015. He started in 2011 with about 150 and it has effectively doubled with each iteration. While everyone has expected eventual consolidation this hasn’t happened to date.

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Scott’s Marketing Technology Landscape – 2016

Why?

For a possible answer, we can look at a fascinating study conducted by a UCLA team looking at the fossil record of cars. Since 1896, there is a reliable record of the introduction of new automobile makes and models. In essence, this creates a “fossil” record, similar to biology, where we can look at the evolution of a technology over an extended time period. In this case, the researchers were looking to isolate the factors that led to the greatest introduction of new models and the discontinuation of old models. When many new models were being introduced, the evolution of the automotive technology accelerated. The researchers wanted to see if this pace of evolution was tied to strength of the economy, changes in oil prices or the number of other cards on the market. What they found was that competition in the marketplace played a bigger role in the variety of car models than either economic growth or oil prices.

However, these periods of rapid innovation didn’t last forever. Inevitably, there was a period of consolidation, where the major manufacturers focused on a few models to increase profitability. It’s a lot more profitable to produce a popular model with relatively few changes over a long period of time.

Once again, we have an oscillation or wave happening.

What is interesting about this is that these periods of rapid innovation always come from an open market with many competitors – exactly what is happening in marketing technology right now. That is because open markets always drive more innovation than can be achieved within hierarchal organizations. As Eric Raymond showed in his brilliant essay on the open source movement – The Cathedral and the Bazaar – the evolutionary forces of a distributed open market (or “Bazaar”) always trump vertical integration (“Cathedrals”) when it comes to spinning off fresh ideas.

In their book “Creative Destruction,” authors Richard Foster and Sarah Kaplan show that organizations (cathedrals) tend to favor incremental innovation with occasional forays into substantial innovation. But markets (bazaars) unleash transformational innovation. The unpredictability and risk increases by a factor of ten as you go from one version of innovation to the other, but so do the rewards. Innovation in markets grow on a logarithmic scale. It’s why some players – like Tesla and Google – have espoused the open-source “Bazaar” approach in areas like sustainable transportation and artificial intelligence where rapid innovation is essential.

There is another critical factor at play here as well. The market/bazaar, being ruthless, quickly culls the competitors down to those that have the best market potential. This explosion of innovation and the subsequent winnowing need a brutally competitive market environment – a rugged landscape in evolutionary terms. Organizations/Cathedrals are reluctant to pull the plug on losers as they fall victim to the sunk cost fallacy and loss aversion. Markets/bazaars operate like nature – “red in tooth and claw” – with a brutal efficiency in dispatching the less fit.

After this explosion of innovation and the subsequent purge, there is a period of consolidation where the biggest players benefit. Let’s call this the Cathedral phase. Here, operational efficiency takes over, looking for greater profitability. Here, market tested innovation is acquired by the largest organizations and systematically incorporated into a replicable template that allows for scalability. Here, the Cathedral model does what it excels at, maximizing profits. Of course, there is a trade off. Innovation withers and dies in this environment, leading to eventual stagnation, which triggers the need for break out innovation all over again.

Will marketing technology follow the Cathedral/Bazaar pattern? In his last landscape, Scott mentioned that rather than coalescing around an “a small oligopoly of platform providers competing for that starring role” the Mar-Tech ecosystem seems to be embedding plug and play compatibility allowing for a longer “Bazaar” phase. Perhaps, with the elimination of market friction, we’re getting to a point where profitability can be uncoupled from the need for scale. I guess we’ll have to wait and see how many mar-tech vendors end up on the 2017 version of Scott’s slide.

 

 

 

 

Survival of the Fittest Revisited

I’ve used the phrase Survival of the fittest in columns in the past. One of these columns ran again last week and sparked a debate that played out in the comment section. It reminded me that this is one of those phrases that everyone uses but not everyone knows what it means. In fact, it’s meaning when used in evolution has morphed over time into something never intended by at least one of it’s early adopters.

When I say “survival of the fittest” you may think that translates to survival of the strongest or fastest or biggest or smartest. But that was never how Mr. Darwin intended it.

The phrase itself didn’t originate with Charles Darwin. It never appeared in the original edition of On the Origin of Species. It came from the British polymath Herbert Spencer, who used the term in 1864 in Principles of Biology. Darwin did approve of it; however, and adopted it in subsequent editions of his book.

For Darwin, the phrase was intended to mean “better designed for an immediate, local environment.” The use of the term “fit” may be leading to the confusion here. We use fit to mean physical superiority. This is where the “faster, bigger, stronger” interpretation came from. But Darwin meant a better “fit” with the environment. The difference is crucial.

Herbert Spencer’s use of the term is probably closer to how it is commonly interpreted today. Spencer applied the concept of evolutionary competition to everything he saw, including economics and sociology. If you follow the phrase’s lineage down this path, we see how the idea of physical superiority became intertwined with the concept of fitness. Unfortunately, this interpretation led to the ethically murky waters of Social Darwinism and cutthroat competition.

Why this semantic lesson of the day? Because I think there’s something important here that serves as a lesson in volatile times. Survival of the fittest is a phrase that’s seldom used by scientists today. Darwin intended it to be a substitute for natural selection, but we now know that the survival of species has little to do with survival between individuals and much more to do with the ability to adapt to sudden changes in the environment or expand into under utilized ecological niches. Those that can pivot quickest to take advantage of environmental opportunities and recover from catastrophic external factors are the ones that will flourish. Survival is not about physical superiority, but rather about adaptability.

When we stick with Darwin’s intended meaning, we discover two amazing things: 1) Physical superiority depends to some extent on a stable playing field; and, 2) The more dynamic the environment, the more important adaptability becomes.

In stable environments where little changes from day to day, natural selection tends to build scale in terms of strength and size. But this building of physical superiority is tied to that environment. The scaling is done on the scaffolding on a stable ecosystem. When that ecosystem changes dramatically (think an asteroid slamming into the earth) the physical advantages that were formed in the previous era can become disadvantages in the new one (think dinosaurs).

In environments where change accelerates, adaptability trumps all. And it’s very rare to see adaptability and scale come in the same package. One is usually sacrificed for the other.

Prospect Theory, Back Burners and Relationship Risk

What does relationship infidelity and consumer behavior have in common? Both are changing, thanks to technology – or, more specifically – the intersection between technology and our brains. And for you regular readers, you know that stuff is right in my wheelhouse.

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Dr. Michelle Drouin

So I was fascinated by a recent presentation given by Dr. Michelle Drouin from Purdue University. She talked about how connected technologies are impacting the way we think about relationship investment.

The idea of “investing” in a relationship probably paints in a less romantic light then we typically think of, but it’s an accurate description. We calculate odds and evaluate risk. It’s what we do. Now, in the case of love, an admittedly heuristic process becomes even less rational. Our subliminal risk appraisal system is subjugated by a volatile cocktail of hormones and neurotransmitters. But – at the end of the day – we calculate odds.

If you take all this into account, Dr. Drouin’s research into “back burners” becomes fascinating, if not all that surprising. In the paper, back burners are defined as “a desired potential or continuing romantic/sexual partner with whom one communicates, but to whom one is not exclusively committed.” “Back burners” are our fall back bets when it comes to relationships or sexual liaisons. And they’re not exclusive to single people. People in committed relationships also keep a stable of “back burners.” Women keep an average of 4 potential “relationship” candidates from their entire list of contacts and 8 potential “liaison” candidates. Men, predictably, keep more options open. Male participants in the study reported an average of over 8 “relationship” options and 26 liaison “back burners.” Drouin’s hypothesis is that this number has recently jumped thanks to technology, especially with the connectivity offered through social media. We’re keeping more “back burners” because we can.

What does this have to do with advertising? The point I’m making is that this behavior is not unique. Humans treat pretty much everything like an open marketplace. We are constantly balancing risk and reward amongst all the options that are open to us, subconsciously calculating the odds. It’s called Prospect Theory. And, thanks to technology, that market is much larger than it’s ever been before. In this new world, our brain has become a Vegas odds maker on steroids.

In Drouin’s research, it appears that new technologies like Tinder, What’sapp and Facebook have had a huge impact on how we view relationships. Our fidelity balance has been tipped to the negative. Because we have more alternatives – and it’s easier to stay connected with those alternatives and keep them on the “back burner” – the odds are worth keeping our options open. Monogamy may not be our best bet anymore. Facebook is cited in one-third of all divorce cases in the U.K. And in Italy, evidence from the social messaging app What’sapp shows up in nearly half of the divorce proceedings.

So, it appears that humans are loyal – until a better offer with a degree of risk we can live with comes along.

This brings us back to our behaviors in the consumer world. It’s the same mental process, applied in a different environment. In this environment, relationships are defined as brand loyalty. And, as Emanuel Rosen and Itamar Simonson show in their book Absolute Value, we are increasingly keeping our options open in more and more consumer decisions. When it comes to buying stuff – even if we have brand loyalty – we are increasingly aware of the “back burners” available to us.

 

 

 

Why Our Brains are Blocking Ads

On Mediapost alone in the last three months, there have been 172 articles written that have included the words “ad blockers” or “ad blocking.” That’s not really surprising, given that Mediapost covers the advertising biz and ad blocking is killing that particular biz, to the tune of an estimated loss of $41 billion in 2016. eMarketer estimates 70 million Americans, or 1 out of every 4 people online, uses ad blockers.

Paul Verna, an eMarketer Senior Analyst said “Ad blocking is a detriment to the entire advertising ecosystem, affecting mostly publishers, but also marketers, agencies and others whose businesses depend on ad revenue.” The UK’s culture Secretary, John Whittingdale, went even further, saying that ad blocking is a “modern-day protection racket.”

Here’s the problem with all this finger pointing. If you’re looking for a culprit to blame, don’t look at the technology or the companies deploying that technology. New technologies don’t cause us to change our behaviors – they enable behaviors that weren’t an option before. To get to the bottom of the growth of ad blocking, we have to go to the common denominator – the people those ads are aimed at. More specifically, we have to look at what’s happening in the brains of those people.

In the past, the majority of our interaction with advertising was done while our brain was idling, with no specific task in mind. I refer to this as bottom up environmental scanning. Essentially, we’re looking for something to capture our attention: a TV show, a book, a magazine article, a newspaper column. We were open to being engaged by stimuli from our environment (in other words, being activated from the “bottom up”).

In this mode, the brain is in a very accepting state. We match signals from our environment with concepts and beliefs we hold in our mind. We’re relatively open to input and if the mental association is a positive or intriguing one – we’re willing to spend some time to engage.

We also have to consider the effect of priming in this state. Priming sets a subconscious framework for the brain that then affects any subsequent mental processing. The traditional prime that was in place when we were exposed to advertising was a fairly benign one: we were looking to be entertained or informed, often the advertising content was delivered wrapped in a content package that we had an affinity for (our favorite show, a preferred newspaper, etc), and advertising was delivered in discrete chunks that our brain had been trained to identify and process accordingly.

All this means that in traditional exposures to ads, our brain was probably in the most accepting state possible. We were looking for something interesting, we were primed to be in a positive frame of mind and our brains could easily handle the contextual switches required to consider an ad and it’s message.

We also have to remember that we had a relatively static ad consumption environment that usually matched our expectations of how ads would be delivered. We expected commercial breaks in TV shows. We didn’t expect ads in the middle of a movie or book, two formats that required extended focusing of attention and didn’t lend themselves to mental contextual task switches. Each task switch brings with it a refocusing of attention and a brief burst of heightened awareness as our brains are forced to reassess its environment. These are fine in some environments – not in others.

Now, let’s look at the difference in cognitive contexts that accompany the deliver of most digital ads. First of all, when we’re online on our desktop or engaged with a mobile device, it’s generally in what I’ll call a “top down foraging” mode. We’re looking for something specific and we have intent in mind. This means there’s already a task lodged in our working memory (hence “top down”) and our attentional spotlight is on and focused on that task. This creates a very different environment for ad consumption.

When we’re in foraging mode, we suddenly are driven by an instinct that is as old as the human race (actually, much older than that): Optimal Foraging Theory. In this mode, we are constantly filtering the stimuli of our environment to see what is relevant to our intent. It’s this filtering that causes attentional blindness to non-relevant factors – whether they be advertising banners or people dressed up like gorillas. This filtering happens on a subconscious basis and the brain uses a primal engine to drive it – the promise of reward or the frustration of failure. When it comes to foraging – for food or for information – frustration is a feature, not a bug.

Our brains have a two loop learning process. It starts with a prediction – what psychologists and economists call “expected utility.” We mentally place bets on possible outcomes and go with the one that promises the best reward. If we’re right, the reward system of the brain gives us a shot of dopamine. Things are good. But if we bet wrong, a different part of the brain kicks in: the right anterior insula, the adjacent right ventral prefrontal cortex and the anterior cingulate cortex. Those are the centers of the brain that regulate pain. Nature is not subtle about these things – especially when the survival of the species depends on it. If we find what we’re looking for, we get a natural high. If we don’t, it’s actually causes us pain – but not in a physical way. We know it as frustration. Its purpose is to encourage us to not make the same mistake twice

The reason we’re blocking ads is that in the context those ads are being delivered, irrelevant ads are – quite literally – painful. Even relevant ads have a very high threshold to get over. Ad blocking has little to do with technology or “protection rackets” or predatory business practices. It has to do with the hardwiring of our brains. So if the media or the ad industry want to blame something or someone, let’s start there.

The Bermuda Triangle of Advertising

In the past few weeks, via the comments I’ve received on my two (1,2) columns looking at the possible future of media selection and targeting, it’s become apparent to me that we’re at a crisis point when it comes to advertising. I’ve been fortunate enough to have some of the brightest minds and sharpest commentators in the industry contributing their thoughts on the topic. In the middle of all these comments lies a massive gap. This gap can be triangulated by looking at three comments in particular:

Esther Dyson: “Ultimately, what the advertisers want is sales…  attention, engagement…all these are merely indicators for attribution and waypoints on the path to sales.”

Doc Searls: “Please do what you do best (and wins the most awards): make ads that clearly sponsor the content they accompany (we can actually appreciate that), and are sufficiently creative to induce positive regard in our hearts and minds.”

Ken Fadner: “I don’t want to live in a world like this one” (speaking of the hyper targeted advertising scenario I described in my last column).

These three comments are all absolutely right (with the possible exception of Searls, which I’ll come back to in a minute) and they draw a path around the gaping hole that is the future of advertising.

So let’s strip this back to the basics to try to find solid ground from which to move forward again.

Advertising depends on a triangular value exchange: We want entertainment and information – which is delivered via various media. These media need funding – which comes from advertising. Advertising wants exposure to the media audience. So, if we boil that down – we put up with advertising in return for access to entertainment and information. This is the balance that is deemed “OK” by Doc Searls and other commenters

The problem is that this is no longer the world we live in – if we ever did. The value exchange requires all three sides to agree that the value is sufficient for us to keep participating. The relatively benign and balanced model of advertising laid out by Searls just doesn’t exist anymore.

The problem is the value exchange triangle is breaking down on two sides – for advertisers and the audience.

As I explained in an earlier Online Spin, value exchanges depend on scarcity and for the audience, there is no longer a scarcity of information and entertainment. Also, there are now new models for information and entertainment delivery that disrupt our assessment of this value exchange. The cognitive context that made us accepting of commercials has been broken. Where once we sat passively and consumed advertising, we now have subscription contexts that are entirely commercial free. That makes the appearance of advertising all the more frustrating. Our brain has been trained to no longer be accepting of ads. The other issue is that ads only appeared in contexts where we were passively engaged. Now, ads appear when we’re actively engaged. That’s an entirely different mental model with different expectations of acceptability.

This traditional value exchange is also breaking down for advertisers. The inefficiencies of the previous model have been exposed and more accountable and effective models have emerged. Dyson’s point was probably the most constant bearing point we can navigate to – companies want sales. They also want more effective advertising. And much as we may hate the clutter and crap that litters the current digital landscape, when it works well it does promise to deliver a higher degree of efficiency.

So, we have the previous three sided value exchange collapsing on two of the sides, bringing the third side – media- down with it.

Look, we can bitch about digital all we want. I share Searls frustration with digital in general and Fadner’s misgivings about creepy and ineffective execution of digital targeting in particular. But this horse has already left the barn. Digital is more than just the flavor of the month. It’s the thin edge of a massive wedge of change in content distribution and consumption. For reasons far too numerous to name, we’ll never return to the benign world of clearly sponsored content and creative ads. First of all, that benign world never worked that well. Secondly, two sides of the value-exchange triangle have gotten a taste of something better- virtually unlimited content delivered without advertising strings attached and a much more effective way to deliver advertising.

Is digital working very well now? Absolutely not. Fadner and Searls are right about that, It’s creepy, poorly targeted, intrusive and annoying. And it’s all these things for the very same reason that Esther Dyson identified – companies want sales and they’ll try anything that promises to deliver it. But we’re at the very beginning of a huge disruptive wave. Stuff isn’t supposed to work very well at this point. That comes with maturity and an inevitable rebalancing. Searls may rail against digital, just like people railed against television, the telephone and horseless carriages. But it’s just too early to tell what a more mature model will look like. Corporate greed will dictate the trying of everything. We will fight back by blocking the hi-jacking of our attention. A sustainable balance will emerge somewhere in between. But we can’t see it yet from our vantage point.

The Rise of the Audience Marketplace

Far be it from me to let a theme go before it has been thoroughly beaten to the ground. This column has hosted a lot of speculation on the future of advertising and media buying and today, I’ll continue in that theme.

First, let’s return to a column I wrote almost a month ago about the future of advertising. This was a spin-off on a column penned by Gary Milner – The End of Advertising as We Know It. In it, Gary made a prediction: “I see the rise of a global media hub, like a stock exchange, which will become responsible for transacting all digital programmatic buys.”

Gary talked about the possible reversal of fragmentation of markets by channel and geographic area due to the potential centralization of digital media purchasing. But I see it a little differently than Gary. I don’t see the creation of a media hub – or, at least – that wouldn’t be the end goal. Media would simply be the means to the end. I do see the creation of an audience market based on available data. Actually, even an audience would only be the means to an end. Ultimately, we’re buying one thing – attention. Then it’s our job to create engagement.

The Advertising Research Foundation has been struggling with measuring engagement for a long time now. But it’s because they were trying to measure engagement on a channel-by-channel basis and that’s just not how the world works anymore. Take search, for example. Search is highly effective at advertising, but it’s not engaging. It’s a connecting medium. It enables engagement, but it doesn’t deliver it.

We talk multi-channel a lot, but we talk about it like the holy grail. The grail in this cause is an audience that is likely to give us their attention and once they do that – is likely to become engaged with our message. The multi-channel path to this audience is really inconsequential. We only talk about multi-channel now because we’re stopping short of the real goal, connecting with that audience. What advertising needs to do is give us accurate indicators of those two likelihoods: how likely are they to give us their attention and what is their potential proclivity towards our offer. The future of advertising is in assembling audiences – no matter what the channel – that are at a point where they are interested in the message we have to deliver.

This is where the digitization of media becomes interesting. It’s not because it’s aggregating into a single potential buying point – it’s because it’s allowing us to parallel a single prospect along a path of persuasion, getting important feedback data along the way. In this definition, audience isn’t a static snapshot in time. It becomes an evolving, iterative entity. We have always looked at advertising on an exposure-by-exposure basis. But if we start thinking about persuading an audience that paradigm needs to be shifted. We have to think about having the right conversation, regardless of the channel that happens to be in use at the time.

Our concept of media happens to carry a lot of baggage. In our minds, media is inextricably linked to channel. So when we think media, we are really thinking channels. And, if we believe Marshall McLuhan, the medium dictates the message. But while media has undergone intense fragmentation they’ve also become much more measurable and – thereby – more accountable. We know more than ever about who lies on the other side of a digital medium thanks to an ever increasing amount of shared data. That data is what will drive the advertising marketplace of the future. It’s not about media – it’s about audience.

In the market I envision, you would specify your audience requirements. The criteria used would not be so much our typical segmentations – demography or geography for example. These have always just been proxies for what we really care about; their beliefs about our product and predicted buying behaviors. I believe that thanks to ever increasing amounts of data we’re going to make great strides in understanding the psychology of consumerism. These  will be foundational in the audience marketplace of the future. Predictive marketing will become more and more accurate and allow for increasingly precise targeting on a number of behavioral criteria.

Individual channels will become as irrelevant as the manufacturer that supplies the shock absorbers and tie rods in your new BMW. They will simply be grist for the mill in the audience marketplace. Mar-tech and ever smarter algorithms will do the channel selection and media buying in the background. All you’ll care about is the audience you’re targeting, the recommended creative (again, based on the mar-tech running in the background) and the resulting behaviors. Once your audience has been targeted and engaged, the predicted path of persuasion is continually updated and new channels are engaged as required. You won’t care what channels they are – you’ll simply monitor the progression of persuasion.

 

NBC’s Grip on Olympic Gold Slipping

When it comes to benchmarking stuff, nothing holds a candle to the quadrennial sports-statzapooloza we call the Summer Olympics. After 3 years, 11 months and 13 days of not giving a crap about sports like team pursuit cycling or half heavyweight judo, we suddenly get into fist fights over 3 one hundredths of a second or an unawarded Yuko.

But it’s not just sports that are thrown into comparative focus by the Olympic games. It also provides a chance to take a snap shot of media consumption trends. The Olympics is probably the biggest show on earth. With the possible exception of the World Cup, it’s the time when the highest number of people on the planet are all watching the same thing at the same time. This makes it advertising nirvana.

Or it should.

Over the past few Olympics, the way we watch various events has been changing because of the nature of the Games themselves. There are 306 separate events in 35 recognized sports that are spread over 16 days of competition. The Olympics play to a global audience, which means that coverage has to span 24 time zones. At any given time, on any given day, there could be 6 or 7 events running simultaneously. In fact, as I’m writing this, diving, volleyball, men’s omnium cycling, Greco-Roman wresting, badminton, field hockey and boxing are all happening at the same time.

This creates a challenge for network TV coverage. The Olympics are hardly a one-size-fits-all spectacle. So, if you’re NBC and you’ve shelled out 1.6 billion dollars to provide coverage, you have a dilemma: how do you assemble the largest possible audience to show all those really expensive ads to? How do you keep all those advertisers happy?

NBC’s answer, it seems, is to repackage the Olympics as a scripted mini-series. It means throttling down real time streaming or live broadcast coverage on some of the big events so these can be assembled into packaged stories during their primetime coverage. NBC’s chief marketing officer, John Miller, was recently quoted as saying, “The people who watch the Olympics are not particularly sports fans. More women watch the games than men, and for the women, they’re less interested in the result and more interested in the journey. It’s sort of like the ultimate reality show and miniseries wrapped into one.”

So, how is this working out for NBC? Not so well, as it turns out.

Ratings are down, with NBC posting the lowest primetime numbers since 1992. The network has come under heavy fire for what is quite possibly the worst Olympic coverage in the history of the games. Let’s ignore for a moment their myopic focus on US contestants and a handful of superstars like Usain Bolt (which may not be irritating unless you’re a international viewer like myself). Their heavy-handed attempt to control and script the fragmented and emergent drama of any Olympic games has stumbled out of the blocks and fallen flat on its face.

I would categorize this as a “RTU/WTF” The first three letters stand for “Research tells us…” I think you can figure out the last three. I’m sure NBC did their research to figure out what they thought the audience really wanted in Olympics game coverage. I’m positive there was a focus group somewhere that told the network what they wanted to hear; “Screw real time results. What we really want is for you to tell us – with swelling music, extreme close ups and completely irrelevant vignettes– the human drama that lies behind the medals…” And, in the collective minds of NBC executives, they quickly added, “…with a zillion commercial breaks and sponsorship messages.”

But it appears that this isn’t what we want. It’s not even close. We want to see the sports we’re interested in, on our device of choice and at the time that best suits us.

This, in a nutshell, is the disruption that is broadsiding the advertising industry at full ramming speed. It was exactly what I was talking about in my last column. NBC may have been able to play their game when they were our only source of information and we were held captive by this scarcity. But over the past 3 Olympic games, starting in Athens in 2004, technology has essentially erased that scarcity. The reality no longer fits NBC’s strategy. Coverage of the Olympics is now a multi-channel affair. What we’re looking for is a way to filter the coverage based on what is most interesting to us, not to be spoon-fed the coverage that NBC feels has the highest revenue potential.

It’s a different world, NBC. If you’re planning to compete in Tokyo, you’d better change your game plan, because you’re still playing like it’s 1996.

 

 

 

Media Buying is Just the Tip of Advertising’s Disruptive Iceberg

Two weeks ago, Gary Milner wrote a lucid prediction of what advertising might become. He rightly stated that advertising has been in a 40-year period of disruption. Bingo. He went on to say that he sees a consolidation of media buying into a centralized hub. Again, I don’t question the clarity of Milner’s crystal ball. It makes sense to me.

What is missing from Milner’s column, however, is the truly disruptive iceberg that is threatening to founder advertising as we know it – the total disruption of the relationship between the advertiser and the marketplace. Milner deals primarily with the media buying aspect of advertising but there’s a much bigger question to tackle. He touched on it in one sentence: “The fact is that a vast majority of advertising is increasingly being ignored.”

Yes! Exactly. But why?

I’ll tell you why. It’s because of a disagreement about what advertising should be. We (the buyers) believe advertising’s sole purpose is to inform. But the sellers believe advertising is there to influence buyers. And increasingly, we’re rejecting that definition.

I know. That’s a tough pill to swallow. But let’s apply a little logic to the premise. Bear with me.

Advertising was built on a premise of scarcity. Market places can’t exist without scarcity. There needs to be an imbalance to make an exchange of value worthwhile. Advertising exists because there once was a scarcity of information. We (the buyers) lacked information about products and services. This was primarily because of the inefficiencies inherent in a physical market. So, in return for the information, we traded something of value – our attention. We allowed ourselves to be influenced. We tolerated advertising because we needed it. It was the primary way we gained information about the marketplace.

In Milner’s column, he talks about Peter Diamandis’ 6 stages that drive the destruction of industries: digitalization, deception, disruption, demonetization, dematerialization, and democratization. Milner applied it to the digitization of media. But these same forces are also being applied to information and rather than driving advertising from disruption to a renaissance period, as Milner predicts, I believe we’ve barely scratched the surface of disruption. The ride will only get bumpier from here on.

The digitization of information enables completely new types of marketplaces. Consider the emergence of the two-sided markets that both AirBNB and Uber exemplify. Thanks to the digitization of information, entirely new markets have emerged that allow the flow of information between buyers and suppliers. Because AirBNB and Uber have built their business models astride these flows, they can get a cut of the action.

But the premise of the model is important to understand. AirBNB and Uber are built on the twin platforms of information and enablement. There is no attempt to persuade by the providers of the platforms – because they know those attempts will erode the value of the market they’re enabling. We are not receptive to persuasion (in the form of advertising) because we have access to information that we believe to be more reliable – user reviews and ratings.

The basic premise of advertising has changed. Information is no longer scarce. In fact, through digitization, we have the opposite problem. We have too much information and too little attention to allocate to it. We now need to filter information and increasingly, the filters we apply are objectivity and reliability. That turns the historical value exchange of advertising on its head. This has allowed participatory information marketplaces such as Uber, AirBNB and Google to flourish. In these markets, where information flows freely, advertising that attempts to influence feels awkward, forced and disingenuous. Rather than building trust, advertising erodes it.

This disruption has also driven another trend with dire consequences for advertising as we know it – the “Maker” revolution and the atomization of industries. There are some industries where any of us could participate as producers and vendors. The hospitality industry is one of these. The needs of a traveller are pretty minimal – a bed, a roof, a bathroom. Most of us could provide these if we were so inclined. We don’t need to be Conrad Hilton. These are industries susceptible to atomization – breaking the market down to the individual unit. And it’s in these industries where disruptive information marketplaces will emerge first. But I can’t build a refrigerator. Or a car (yet). In these industries, scale is still required. And these will be the last strongholds of mass advertising.

Milner talked about the digitization of media and the impact on advertising. But there’s a bigger change afoot – the digitization of information in marketplaces that previously relied on scarcity of information to prop up business models. As information goes from scarcity to abundance, these business models will inevitably fall.

Where Context Comes From

Fellow Spinner Cory Treffiletti told you last week that data without context is noise.

Absolutely right.

I want to continue that conversation, because it’s an important one. It’s all about context. So let’s talk a little more about context. And specifically how we decide what makes up that context.

You might have seen or heard the hubbub that emerged around a tweet from Neil Degrasse Tyson a month ago: “Earth needs a virtual country: #Rationalia, with a one-line Constitution: All policy shall be based on the weight of evidence”

Nice thought, but it ignited a social media shit-storm. Which was entirely predictable. Because we don’t want to be rational. We want to be human. Did 79 episodes of Star Trek teach us nothing?

The biggest beef against #Rationalia was that evidence is typically in the eyes of the beholder. It’s all a matter of context. I’m guessing that the policies that come from evidence in the hands of Republicans will not bear much resemblance to policies that come from the evidence of Democrats. The evidence could be the same but the context is different, because Democrats and Republicans think differently.

Like Treffiletti said – evidence without context is just noise. And our context is only marginally based on evidence. And that’s why #Rationalia – as intellectually attractive as it might be – won’t work.

We as humans understand the world through something called sense making. This is the process we use to build context. In 2006, psychologist Gary Klein shed new light on how we make sense of the world. We start with a frame that captures our current understanding of the situation and depending on the evidence presented to us, we decide whether to elaborate our frame or discard it and create a new frame. So, sensemaking is really an iterative loop that is constantly using our current frame as a reference point.

But here’s the thing. What we consider as evidence depends on the frame we already have in place. It’s the filter that determines what data we pay attention to. And much as Neil Degrasse Tyson would like the governments of the world to be totally unbiased in the filtering of evidence, “that dog just won’t hunt.” It can’t – because we can’t consider data without some context to put it in.

Perhaps someday artificial intelligence will advance to the point where it can pull unbiased context out of random data. Maybe computers will be able to do what we’re unable to – make sense of the noise without assuming a pre-existing frame. But we’re not there yet. And even if we were, we would simply look at the conclusions of the computer and decide whether we agree with them or not. As long as humans are in charge, there will always be a biased filter in place.

So back to Cory’s column. If context is so important, think about where that context is coming from. Who is defining the context and what frame are they operating from? That in turn will define what data you consider and how you consider it.

Perhaps the most important decision before considering data is to be totally clear about what the goal is. Goals, together with experience, form the underpinning of beliefs. Frames are then built on those beliefs. Context comes from those frames. And context is the filter we apply to evidence.