157 Shades of Grey…

Design is important. Thinking through how people will respond to the aesthetics of your product is an admirable thing. I remember once having the pleasure of sharing a stage with JetBlue’s VP of Marketing – Amy Curtis-McIntyre. She was explaining how important good design was to the airline’s overall marketing strategy. A tremendous amount of thought went into the aesthetics of all their printed materials – even those cards explaining the safety features of the airplane that none of us ever read. But on JetBlue, not only did passengers read them – they stole them because they were so cleverly designed. Was this a problem for management? Not according to Amy:

“You know you’re doing something right when people steal your marketing shit”

So, I’m a fan of good design. But according to a recent story on Fastcodesign.com, Google is going at least 156 shades too far. They seem obsessed with color – or – at least, testing for colors. The design team for Google’s new home assistant – the Mini – had to pick three different colors for the home appliance. They wanted one to make a personal statement and apparently that statement is best made by the color “Coral.” Then they needed a color that would sit unobtrusively next to your TV set and that turned out to be “Charcoal.” Finally, they needed a “floater” color that could go anywhere in the house, including the kitchen. And that’s when the design team at Google may have gone off the tracks. They tested 157 shades of grey – yes – 157 – before they settled on “Chalk,” which is said to be the most inoffensive shade imaginable. They even worked with a textile firm to create their own custom cloth for the grill on top.

That beats Google’s previous obsessive-compulsive testing disorder record, set by then VP of Search Marissa Mayer when she ordered the design team to test 42 different shades of blue for search links to see which got the most clicks. At Google, good design seems to equal endless testing. But is there anything wrong with that?

Well, for one thing, you can test yourself into a rabbit hole, running endless tests and drowning in reams of data looking for the optimal solution – completely missing global maxima while myopically focused on the local. Google tests everything – and I mean everything – truly, madly and deeply. Even Google insiders admit this penchant for testing often gets them focused on the trees rather than the forest. This is particularly true for design. Google has a long history of obsessively turning out ho-hum designs.

Personally, when it comes to pure design magic, I much prefer the Apple approach. Led by Steve Job and Jon Ive’s unerring sense for the aesthetic – it’s hard to think of a longer run of spectacular product designs. Yes, they too sweated the small stuff. But those details were always in service of a higher vision – an empathetic, elegantly simple, friendly approach to product design that somehow magically connected with the user, leaving that user somewhat awed and consistently impressed. One might quibble with the technology that lies inside the package, but no one has put together a more beautiful package that the Apple design team at the height of their powers.

When you look at a Google product, you have the result of endless testing and data crunching. When you look at a classic Apple design, you sense that this came from more than simple testing. This came from intuition and creativity.


I, Robot….

Note: No Artificial Intelligence was involved in the creation of this column.

In the year 1942, science fiction writer Isaac Asimov introduced the 3 Rules of Robotics in his collection of short stories, I, Robot..

  1. A robot may not injure a human being or, through inaction, allow a human being to come to harm.
  2. A robot must obey the orders given it by human beings except where such orders would conflict with the First Law.
  3. A robot must protect its own existence as long as such protection does not conflict with the First or Second Laws.

Asimov had the rules as coming from the Handbook of Robotics, 56th Edition, 2058 A.D. What was once an unimaginably distant time in the future is now knocking with increasing intensity on the door of the present. And Elon Musk, for one, is worried. “AI is a fundamental risk to the existence of human civilization.” Musk believes, Rules of Robotics or no, we won’t be able to control this genie once it gets out of its bottle.

Right now, the genie looks pretty benign. In the past year, the Washington Post has used robot reporters to write over 850 stories. The Post believes this is a win/win with their human reporters, because the robot, named Heliograf, can:

  • Cover stories that wouldn’t have been covered due to lack of human resources
  • Do the factual heavy lifting for human reporters
  • Alert humans to possible news stories in big data sets

So, should we fear or cheer robots? I think the Post’s experiment highlights two areas that AI excels at, and indicates how we might play nice with machines.

For AI to work effectively, the dots have to be pretty well sketched out. When they are, AI can be tireless in scouting out relevant facts and data where humans would tend to get bored easily. But humans are still much better at connecting those dots, especially when no obvious connection is apparent. We do it through something called intuition. It’s at least one area where we can still blow machines away.

Machines are also good at detecting patterns in overwhelming amounts of data. Humans tend to overfit…make the data fit our narratives. We’ll come back to this point in a minute, but for now, let’s go back to intuition. It’s still the trump card we humans hold. In 2008, Wired editor Chris Anderson prematurely (and, many believe, incorrectly) declared the Scientific Method dead, thanks to the massive data sets we now have available:

“We can analyze the data without hypotheses about what it might show. We can throw the numbers into the biggest computing clusters the world has ever seen and let statistical algorithms find patterns where science cannot.”

Anderson gets it partly right, but he also unfairly gives intuition short shrift. This is not a zero sum game. Intuition and A.I. can and should play nicely together. As I mentioned a few weeks ago, human intuition was found to boost the effectiveness of an optimization algorithm by 25%.

Evolutionary biologist Richard Dawkins recently came to the defense of intuition in Science, saying:

“Science proceeds by intuitive leaps of the imagination – building an idea of what might be true, and then testing it”

The very human problem comes when we let our imaginations run away from the facts, bending science to fit our hypotheses:

“It is important that scientists should not be so wedded to that intuition that they omit the very important testing stage.”

There is a kind of reciprocation here – an oscillation between phases. Humans are great at some stages – the ones that require intuition and imagination -and machines are better at others – where a cold and dispassionate analysis of the facts is required. Like most things in nature that pulse with a natural rhythm, the whole gains from the opposing forces at work here. It is a symphony with a beat and a counterbeat.

That’s why, for the immediate future anyway, machines should bend not to our will, but to our imagination.

The Assisted Reality of the New Marketer

Last week, MediaPost’s Laurie Sullivan warned us that the future of analytical number crunchers is not particularly rosy in the world of marketing. With cognitive technologies like IBM’s Watson coming on strong in more and more places, analytic skills are not that hot a commodity any more. Ironically, when it comes to marketing, the majority of companies have not planned to incorporate cognitive technologies in the near future. According to a report from IBM and Oxford Economics, only 24% of the organizations have a plan to incorporate CT in their own operations.

Another study, from Forrester, explored AI Marketing Readiness in Retail and eCommerce sectors. The state of readiness is a little better. In these typically forward thinking sectors, 72% are implementing AI marketing tech in the next year, but only 45% of those companies would consider themselves as excelling in at least 2 out of 3 dimensions of readiness.

If those numbers seem contradictory, we should understand what the difference between cognitive technology and artificial intelligence is. You’ll notice that IBM refers to Watson as “cognitive computing.” As Rob High, IBM’s CTO for Watson put it, “What it’s really about is involvement of a human in the loop,” and he described Watson as “augmented intelligence” rather than artificial intelligence.

That “human in the loop” is a critical difference between the two technologies. Whether we like it or not, machines are inevitable in the world of marketing, so we’d better start thinking about how to play nice with them.


I remember first seeing a video from the IBM Amplify summit at a MediaPost event last year. Although the presentation was a little stilted, the promise was intriguing. It showed a marketer musing about a potential campaign and throwing “what ifs” at Watson, who quickly responded with the almost instantly analyzed quantified answers. The premise of the video was to show how smart Watson was. But here’s a “what if” to consider. What if the real key to this was the hypotheticals that the human seemed to be pulling out of the blue? That doesn’t seem that impressive to us – certainly not as impressive as Watson’s corralling and crunching of relevant numbers in the blink of an eye. Musing is what we do. But this is just one example of something called Moravec’s Paradox.

Moravec’s Paradox, as stated by AI pioneer Marvin Minsky, is this: “In general, we’re least aware of what our minds do best. We’re more aware of simple processes that don’t work well than of complex ones that work flawlessly.” In other words, what we find difficult are the tasks that machines are well suited for, and the things we’re not even aware of are the things machines find notoriously hard to do. Things like intuition. And empathy. If we’re looking at the future of the human marketer, we’re probably looking at those two things.

In his book, Humans are Underrated, Geoff Colvin writes,

“Rather than ask what computers can’t do, it’s much more useful to ask what people are compelled to do—those things that a million years of evolution cause us to value and seek from other humans, maybe for a good reason, maybe for no reason, but it’s the way we are.”

We should be ensuring that both humans and machines are doing what they do best, essentially erasing Moravec’s Paradox. Humans focus on intuition and empathy and machines do the heavy lifting on the analyzing and number crunching. The optimal balance – at this point anyway – is a little bit of both.

In Descarte’s Error – neurologist Antonio Damasio showed that without human intuition and emotion – together with the corresponding physical cues he called somatic markers – we could rationalize ourselves into a never-ending spiral without ever coming to a conclusion. We need to be human to function effectively.

Researchers at MIT have even tried to include this into an algorithm. In 1954, Herbert Simon introduced a concept called bounded rationality. It may seem like this puts limits on the cognitive power of humans, but as programmers like to say, bounded rationality is a feature, not a bug. The researchers at MIT found that in an optimization challenge, such as finding the optimal routing strategy for an airline, humans have the advantage of being able to impose some intuitive limits on the number of options considered. For example, a human can say, “Planes should visit each city at the most once,” and thereby dramatically limit the number crunching required. When these intuitive strategies were converted to machine language and introduced into automated algorithms, those algorithms got 10 to 15% smarter.

When it comes right down to it, the essence of marketing is simply a conversation between two people. All the rest: the targeting, the automation, the segmentation, the media strategy – this is all just to add “mass” to marketing. And that’s all the stuff that machines are great at. For us humans, our future seems to rely on our past – and on our ability to connect with other humans.

Disruption in the Rear View Mirror

Oh..it’s so easy to be blasé. I always scan the Mediapost headlines each week to see if there’s anything to spin. I almost skipped right past a news post by Larissa Faw – Zenith: Google Remains Top-Ranked Media Company By Ad Revenue

“Of course Google is the top ranked media company,” I yawned as I was just about to click on the next email in my inbox. Then it hit me. To quote Michael Bublé, “Holy Shitballs, Mom!”

Maybe that headline doesn’t seem extraordinary in the context of today, but I’ve been doing this stuff for almost 20 years now, and in that context – well-it’s huge! I remembered a column I wrote ages ago about speculating that Google had barely scratched its potential. After a little digging, I found it. It was in October, 2006, so just over a decade ago. Google had just passed the 6 billion dollar mark in annual revenue. Ironically, that seemed a bigger deal then their current revenue of almost $80 billion seems today. In that column, I pushed to the extreme and speculated that Google could someday pass $200 billion in revenue. While we’re still only 1/3 of the way there, the claim doesn’t seem nearly as ludicrous as it did back then.

But here’s the line that really made me realize how far we’ve come in the ten and a half years since I wrote that column: “Google and Facebook together accounted for 20% of global advertising expenditure across all media in 2016, up from 11% in 2012. They were also responsible for 64% of all the growth in global ad spend between 2012 and 2016.”

Two companies that didn’t exist 20 years ago now account for 20% of all global advertising expenditure. And the speed with which they’re gobbling advertising budgets is accelerating. If you’re a dilettante student of disruption, as I am, those are pretty amazing numbers. In the day-to-day of Mediapost – and digital marketing in general – we tend to accept all this as normal. It’s like we’re surfing on top of a wave without realizing the wave is 300 freakin’ feet high. Sometimes, you need to zoom out a little to realizing how momentous the every day is. And if you look at this on a scale of decades rather than days, you start to get a sense that the speed of change is massive.

To me, the most interesting thing about this is that both Google and Facebook have introduced a fundamentally new relationship between advertising and it’s audience. Google’s outré is – of course – intent based advertising. And Facebook’s is based on socially mediated network effects. Both of these things required the overlay of digital connection. That – as they say – has made all the difference. And there is where the real disruption can be found. Our world has become a fundamentally different place.

Much as we remain focused on the world of advertising and marketing here in our little corner of the digital world, it behooves us to remember that advertising is simply a somewhat distorted reflection of the behaviors of the world in general. It things are being disrupted here, it is because things are being disrupted everywhere. As it regards us beings of flesh, bone and blood, that disruption has three distinct beachheads: the complicated relationship between our brains and the digital tools we have at our disposal, the way we connect with each other, and a dismantling of the restrictions of the physical world at the same time we build the scaffolding of a human designed digital world. Any one of these has the potential to change our species forever. With all three bearing down on us, permanent change is a lead-pipe cinch.

Thirty years is a nano-second in terms of human history. Even on the scale of my lifetime, it seems like yesterday. Reagan was president. We were terrorized by the Unabomber. News outlets were covering the Iran-Contra affair. U2 released the Joshua Tree. Platoon won the best picture Oscar. And if you wanted to advertise to a lot of people, you did so on a major TV network with the help of a Madison Avenue agency. 30 years ago, nothing of which I’m talking about existed. Nothing. No Google. No Facebook. No Internet – at least, not in a form any of us could appreciate.

As much as advertising has changed in the past 30 years, it has only done so because we – and the world we inhabit – have changed even more. And if that thought is a little scary, just think what the next 30 years might bring.

Want to be Innovative? Immerse Yourself!

In a great post earlier this year, VC Pascal Bouvier (along with Aldo de Jong and Harry Wilson) deconstructed the idea that starts ups always equate with successful innovation. Before you jump on the Lean Start Up bandwagon, realize the success rate of a start up taking ideas to market is about 0.2%. Those slow-moving, monolithic corporations that don’t realize they’re the walking dead? Well, they’re notching a 12.5% hit rate. Sure, they’re not disrupting the universe, but they are protecting their profit margin, and that’s the whole point.

The problem, Bouvier states, is one of context. Start-ups serve a purpose. So do big corporations. But it’s important to realize the context in which they both belong. We are usually too quick to adopt something that appears to be working without understanding why. We then try to hammer it into a place it doesn’t belong.

Start-ups are agents in an ecosystem. Think of them like amino acids in a primordial soup from which we hope, given the right circumstances, life might emerge. The advantage in this market-based ecosystem is that things move freely – without friction. Agents can bump up against each other quickly and catalysts can take their shot at sparking life. It is a dynamic, emergent system. Start-ups are lean and fast-moving because they have to be. It is the blueprint for their survival. It is also why the success rate of any individual start-up is so low. The market is a Darwinian beast – red of tooth and claw. Losers are ruthlessly weeded out.

A corporation is a different beast that occupies a different niche on the evolutionary timeline. It is a hierarchy of components that has already been tested by the market and has assembled itself into a replicable, successful entity. It is a complex organism and has discovered rules that allow it to compete in its ecosystem as a self-organized, vertically integrated, hopefully sustainable entity. In this way, it bears almost no resemblance to a start up. Nor should it.

This is why it’s such a daunting proposition for a start up to transition into a successful corporation. Think of the feat of self-transformation that is required here. Not only do you have to change your way of doing things – you have to change your very DNA. You have to redefine every aspect of who you are, what you do and how you do it.

If you pull out your perspective dramatically here, you see that this is a wave. Call it Schumpeterian Gale of Creative Destruction, call it a Kontdratiev Wave, call it whatever you like – this is not simply a market adaptation – this is a phase transition. The rules on one side of the wave are completely different than on the other side – just as the rules of physics are different for liquids and gases. And that applies to everything, including how you think about innovation.

We commonly believe start-ups are more innovative than corporations. But that’s not actually true. It’s the market that is more innovative. And that innovation has a very distinct characteristic. It comes from agents who are immersed in a particular part of the market. As Bouvier points out in his post, start up CEO’s solve a problem that’s “right in front of their nose.” Think of the typical start up founder. They are ear lobe deep in whatever they are doing. From this perspective, they see something they believe to be a need. They then set out to create a new solution to that need. This is the sense making cycle I keep talking about.

For a lot of start ups, sense making is ingrained. The entrepreneur is embedded in a context where it allows them to make sense of a need that has been overlooked. The magic happens when the switch clicks and the need is matched with a solution. Entrepreneurs are the synaptic connections of the market, but this requires deep immersion in the market.

There’s something else about this immersion that’s important to consider – there is nothing quantitative about it. It’s organic and natural. It’s messy and often chaotic. It’s what I call “steeping in it.” I believe this is also important to innovation. And it’s not just me. A recent study from the University of Toronto shows that creativity thrives in environments free of too much structured knowledge. The authors note, “A hierarchical information structure, compared to a flat information structure, will reduce creativity because it reduces cognitive flexibility.”

Innovation requires insight, and insight comes from being intimately immersed in something. There is a place for data analysis and number crunching, but like most things, that’s the other side of the quant/qual wave. You need both to be innovative.


The Chaos Theory of Marketing

Last week, I wrote why marketers are struggling with job security. In an effort to provide career counseling to an industry, I would offer this suggestion: start learning about the behaviors of non-linear dynamic systems. You’re going to have to get comfortable with the special conditions that accompany complexity.

Markets are always complex, but there’s a phenomenon that gives them the illusion of predictability. This phenomenon is potential. Potential, in this instance, means the gap between the current market state and a possible future state. The presence of potential creates market demand. Every time a new product is introduced, a new potential gap is created. Supply and demand are knocked out of balance. Until balance is regained, the market becomes more predictable.

Here’s an analogy that makes it a little easier to understand how this potential can impact the behaviors of a complex market. A model that’s often used to explain complexity is to imagine a pool table filled with balls. The twist is that each of these balls is self propelled and can move in any direction at random. Imagine how difficult it would be to predict where any single ball might go.

Now, imagine taking this same pool table and lifting one of the corner legs up 6 inches, introducing the force of gravity as a variable. Individual predictions are still difficult, but you’d be pretty safe in saying that the pocket that was diagonally opposite to the raised leg would eventually collect more than it’s fair share of balls. In this example, gravity plays the role of market potential. The market still behaves in a complex manner but there is a consistent force – the force of gravity – that exerts its influence on that complexity and makes it more predictable.

Marketing is built on exploiting potential – on capitalizing on (or creating) gaps between what we have and what we want. These gaps have always been around, but the nature of them has changed. While this potential was aimed further down Maslow’s hierarchy, it was pretty easy to predict purchasing behaviors. When it comes to the basics – meeting our need of food, water, shelter, safety – humans are all pretty much alike. But when it comes to purchases higher up the hierarchy – at the levels of self-esteem or self-actualization – things become tougher to predict.

Collectively, the western world has moved up Maslow’s hierarchy. A 2011 study from Heritage.org showed that even those living below the poverty line have a standard of life that exceeds those at all but the highest income levels just a few decades before. In 2005, 98.7% of homes had a TV, 84% had air conditioning, 79% has satellite or cable TV and 68% had a personal computer.

But it’s not only the diversification of consumer demand that’s increasing the complexity of markets. The more connected that markets become, the more unpredictable they become. Let’s go back to our overly simplified pool ball analogy. Let’s imagine that not only are our pool balls self-propelled, but they also tend to randomly change direction every time they collide with another ball. The more connected the market, the greater the number of collisions and subsequent direction changes. In marketing, those “collisions” could be a tweet, a review, a Facebook post, a Google search – well – you get the idea. It’s complex.

These two factors; the fragmentation of consumer demand and the complexity of a highly interconnected market, makes predicting consumer behavior a mug’s game. The challenge here is that marketing – in a laudable attempt to become more scientific – is following in science’s footsteps by taking a reductionist path. Our marketing mantra is to reduce everything down to testable variables and there’s certainly nothing wrong with that. I’ve said it myself on many occasions. But, as with science, we must realize that when we’re dealing with dynamic complexity, the whole can be much greater than the sum of its testable parts. There are patterns that can be perceived only at a macro scale. Here there be “black swans.” It’s the old issue of ignoring the global maxima or minima by focusing too closely on the local.

Reduction and testing tends to lead to a feeling of control and predictability. And, in some cases (such as a market that has a common potential) things seem to go pretty much according to plan. But sooner or later, complexity rears its head and those best laid plans blow up in your face.



How Vision and Strategy Can Kill a Marketer’s Job Security

“Apparently, marketers today are losing confidence in their ability to meet key goals, like reaching the right customers with their marketing efforts, or being able to understand or evaluate the ROI of their marketing plans.”

Dave Morgan – Why Are Marketing Losing Confidence in Their Ability to Do Their Jobs?

“I think marketing is going to be getting much, much easier over the next couple of years.”

Cory Treffiletti – CMOs’ Vision Crucial to their Success

A couple of weeks ago, my fellow Spinners offered these two seemingly contradictory prognoses of the future of marketing. The contradiction, I believe, is in the conflation of the ideas of media buying and marketing. Yes, media buying is going to get easier (or, at least, more automated). And I agree with Cory’s prediction of consolidation in the industry. But that doesn’t do much to ease the crisis of confidence mentioned by Dave Morgan. That’s still very real.

The problem here is one of complexity. Markets are now complex. Actually, they’ve always been complex, but now they’re even more complex and we marketers can no longer pretend that they’re otherwise. When things get complex, our ability to predict outcomes takes a nosedive.

At the same time, an avalanche of available data makes marketers more accountable than ever. This data, along with faster, smarter machines, offers the promise of predictability, but it’s a dangerous illusion. If anything, the data and AI is just revealing more of the complexity that lurks within those markets.

And here is the crux of the dilemma that lives between the two quotes above. Yes, marketing is becoming more powerful, but the markets themselves are becoming more unpredictable. And marketers are squarely caught on the horns of that dilemma. We sign on to deliver results and when those results are no longer predictable, we feel our job security rapidly slipping away.

Cory Treffiletti talks about vision – which also goes by the name of strategy. It sounds good, but here’s the potential problem with that. In massively complex environments, strategy in the wrong hands can become a liability. It leads to an illusion of control, which is part of a largely disproven and outdated corporate mindset. You can blindly follow a strategy right into a dead end because strategies depend on beliefs and beliefs can dramatically alter your perception of what’s real. No one can control a complex environment. The best you can do is monitor and react to that environment. Of course, those two things can – and should – become a strategy in and of themselves.

Strategy is not dead. It can still make a difference. But it needs to be balanced with two other “S’s” – Sense making and Synthesis. These are the things that make a difference in a world of complexity.

You have to make sense of the market. And this is more difficult than it sounds. This is where the “Strategy” paradox can creep up and kill you. If your “Vision” – to use Cory Treffiletti’s term – becomes more important to you than reality, you’ll simply look for things that confirm that vision and plunge ahead, unaware of the true situation. You’ll ignore the cues that are telling you a change of direction may be required. The Sense Making cycle starts with a “frame” of the world (a.k.a. “Vision”) and then looks for external data to either confirm and elaborate or refute that frame/vision. But the data we collect and the way we analyze that data depends on the frame we begin with. Belief tends to make this process a self-reinforcing loop that often leads to disaster. The stronger the “vision,” the greater the tendency for us to delude ourselves.


Sensemaking: Klein, Moon and Hoffman

If you can remain objective as possible during the sense making cycle you then end up with a reasonably accurate “frame” of your market. This is when the Synthesis part of the equation takes over. Here, you look at your strategy and see how it lines up with the market. You look for new opportunities and threats. Knowing the market is unpredictable, you take the advice of Antifragile author Nassim Nicholas Taleb, minimizing your downside and maximizing your upside. You pull this together into a new iteration of strategy and execute like hell against it. Then you start all over again.

By going through this cycle, you’ll find that you create a wave-like approach to strategy, oscillating through phases of sense making, synthesis and strategic execution. The behavior and mindsets required in each of these phases are significantly – and often diametrically – different. It’s a tough act to pull off.

No wonder marketers are having a tough time right now.