The Status Quo Bias – Why Every B2B Vendor has to Understand It

It’s probably the biggest hurdle any B2B vendor has to get over. It’s called the Status Quo bias and it’s deadly in any high-risk purchase scenario. According to Wikipedia, the bias occurs when the current baseline (or status quo) is taken as a reference point, and any change from that baseline is perceived as a loss. In other words, if it ain’t broke don’t fix it. We believe that simply because something exists, it must have merit. The burden of proof then falls on the vendor to overcome this level of complacency

The Status Quo Bias is actually a bundle of other common biases, including the Endowment Effect, the Loss Aversion Bias, The Existence Bias, Mere Exposure effect and other psychological factors that tend to continually jam the cogs of B2B commerce. Why B2B? The Status Quo Bias is common in any scenario where risk is high and reward is low, but B2B in particular is subject to it because these are group-buying decisions. And, as I’ll soon explain, groups tend to default to Status Quo bias with irritating regularity. The new book from CEB (recently acquired by Gartner) – The Challenger Customer – is all about the status quo bias.

So why is the bias particularly common with groups? Think of the dynamics at play here. Generally speaking, most people have some level of the Status Quo Bias. Some will have it more than others, depending on their level of risk tolerance. But let’s look at what happens when we lump all those people together in a group and force them to come to a consensus. Generally, you’re going to have a one or two people in the group that are driving for change. Typically, these will be the ones that have the most to gain and have a risk tolerance threshold that allows the deal to go forward. On the other end of the spectrum you have some people who have low risk tolerance levels and nothing to gain. They may even stand to lose if the deal goes forward (think IT people who have to implement a new technology). In between you have the moderates. The gain factor and their risk tolerance levels net out to close to zero. Given that those that have something to gain will say yes and those who have nothing to gain will say no, it’s this middle group that will decide whether the deal will live or die.

Without the Status Quo bias, the deal might have a 50/50 chance. But the status quo bias stacks the deck towards negative outcomes for the vendor. Even if it tips the balance just a little bit towards “no” – that’s all that’s required to stop a deal dead in its tracks. The more disruptive the deal, the greater the Status Quo Bias. Let’s remember – this is B2B. There are no emotional rewards that can introduce a counter acting bias. It’s been shown in at least one study (Baker, Laury, Williams – 2008) that groups tend to be more risk averse than the individuals that make up that group. When the groups start discussing and – inevitably – disagreeing, it’s typically easier to do nothing.

So, how do we stick handle past this bias? The common approach is to divide and conquer – identifying the players and tailoring messages to speak directly to them. The counter intuitive finding of the CEB Challenger Customer research was that dividing and conquering is absolutely the wrong thing to do. It actually lessens the possibility of making a sale. While this sounds like it’s just plain wrong, it makes sense if we shift our perspective from the selling side to the buying side.

With our vendor goggles on, we believe that if we tailor messaging to appeal to every individual’s own value proposition, that would be a way to build consensus and drive the deal forward. And that would be true, if every member of our buying committee was acting rationally. But as we soon see when we put on the buying googles, they’re not. Their irrational biases are firmly stacked up on the “do nothing” side of the ledger. And by tailoring messaging in different directions, we’re actually just giving them more things to disagree about. We’re creating dysfunction rather than eliminating it. Disagreements almost always default back to the status quo, because it’s the least risky option. The group may not agree about much, but they can agree that the incumbent solution creates the least disruption.

So what do you do? Well, I won’t steal the CEB’s thunder here, because the Challenger Customer is absolutely worth a read if you’re a B2B vendor. The authors, Brent Adamson, Matthew Dixon, Pat Spenner and Nick Toman, lay out step by step strategy to get around the Status Quo bias. The trick is to create a common psychological frame where everyone can agree that doing nothing is the riskiest alternative. But biases are notoriously sticky things. Setting up a commonly understood frame requires a deep understanding of the group dynamics at play. The one thing I really appreciate about CEB’s approach is that it’s “psychologically sound.” They make no assumptions about buyer rationality. They know that emotions ultimately drive all human behavior and B2B purchases are no exception.

We’re Becoming Intellectually “Obese”

Humans are defined by scarcity. All our evolutionary adaptations tend to be built to ensure survival in harsh environments. This can sometimes backfire on us in times of abundance.

For example, humans are great at foraging. We have built-in algorithms that tell us which patches are most promising and when we should give up on the patch we’re in and move to another patch.

We’re also good at borrowing strategies that evolution designed for one purpose and applying them for another purpose. This is called exaptation. For example, we’ve exapted our food foraging strategies and applied them to searching for information in an online environment. We use these skills when we look at a website, conduct an online search or scan our email inbox. But as we forage for information – or food – we have to remember, this same strategy assumes scarcity, not abundance.

Take food for example. Nutritionally we have been hardwired by evolution to prefer high fat, high calorie foods. That’s because this wiring took place in an environment of scarcity, where you didn’t know where your next meal was coming from. High fat, high calorie and high salt foods were all “jackpots” if food was scarce. Eating these foods could mean the difference between life and death. So our brains evolved to send us a reward signal when we ate these foods. Subsequently, we naturally started to forage for these things.

This was all good when our home was the African savannah. Not so good when it’s Redondo Beach, there’s a fast food joint on every corner and the local Wal-Mart’s shelves are filled to overflowing with highly processed pre-made meals. We have “refined” food production to continually push our evolutionary buttons, gorging ourselves to the point of obesity. Foraging isn’t a problem here. Limiting ourselves is.

So, evolution has made humans good at foraging when things are scarce, but not so good at filtering in an environment of abundance. I suspect the same thing that happened with food is today happening with information.

Just like we are predisposed to look for food that is high in fats, salt and calories, we are drawn to information that:

  1. Leads to us having sex
  2. Leads to us having more than our neighbors
  3. Leads to us improving our position in the social hierarchy

All those things make sense in an evolutionary environment where there’s not enough to go around. But, in a society of abundance, they can cause big problems.

Just like food, for most of our history information was in short supply. We had to make decisions based on too little information, rather than too much. So most of our cognitive biases were developed to allow us to function in a setting where knowledge was in short supply and decisions had to be made quickly. In such an environment, these heuristic short cuts would usually end up working in our favor, giving us a higher probability of survival.

These evolutionary biases become dangerous as our information environment becomes more abundant. We weren’t built to rationally seek out and judiciously evaluate information. We were built to make decisions based on little or no knowledge. There is an override switch we can use if we wish, but it’s important to know that just like we’re inherently drawn to crappy food, we’re also subconsciously drawn to crappy information.

Whether or not you agree with the mainstream news sources, the fact is that there was a thoughtful editorial process, which was intended to improve the quality of information we were provided. Entire teams of people were employed to spend their days rationally thinking about gathering, presenting and validating the information that would be passed along to the public. In Nobel laureate Daniel Kahneman’s terminology, they were “thinking slow” about it. And because the transactional costs of getting that information to us was so high, there was a relatively strong signal to noise ratio.

That is no longer the case. Transactional costs have dropped to the point that it costs almost nothing to get information to us. This allows information providers to completely bypass any editorial loop and get it in front of us. Foraging for that information is not the problem. Filtering it is. As we forage through potential information “patches” – whether they be on Google, Facebook or Twitter – we tend to “think fast” – clicking on the links that are most tantalizing.

I would have never dreamed that having too much information could be a bad thing. But most of the cautionary columns that I’ve written about in the last few years all seem to have the same root cause – we’re becoming intellectually “obese.” We’ve developed an insatiable appetite for fast, fried, sugar-frosted information.

 

Searching for Leaders

I was planning on writing a very erudite column on how our consumption of news has drastically changed when I decided to do a research check on Google Trends and found something interesting. It should come as no surprise to learn that Donald Trump is dominating news searches on Google. But what was surprising was that the number one audience with an appetite for “Trumpie Tidbits” is Canadians. That’s right, my fellow countrymen can’t get enough of the guy. We, as a nation, search more for news on Donald Trump than any other place on earth, even the U.S. We out search you Americans on Google by margin of almost 25% (mind you, that margin reverses for web searches for Trump, but we’re still number 2 in the world).

Why?

I could offer some psychologically plausible reasons having to do with morbid curiosity, voyeurism, schadenfreude or even the Stockholm Syndrome, but honestly I have no idea why we’re submitting ourselves to this. Maybe it’s giving us something to do during our abnormally long winters and seeing as we’re already miserable as hell, we feel we have nothing to lose?

This is somewhat ironic, given that according to several highly reputable online polls, we have the hottest leader in the world right now – one Monsieur Trudeau. But even as photogenic as Justin is, when it comes to launching a Google search, our vote still goes to Trump. When you compare searches for Trump during his election to searches for Trudeau during his election – in Canada, no less – Trump wins by a margin of 2 to 1.

But it’s not just us. Trump’s domination of the search zeitgeist is historic. Google shows relative volumes – with 100 representing the peak popularity. For Trump, this peak corresponded with his election, in November. A second peak, at 65, came with his inauguration. Never in the entire length of Barack Obama’s presidency did he ever come close to this. The nearest was during his first election in 2008, when he peaked at 55. So, in one category at least, Trump would be accurate in claiming a historic win.

I thought I’d see if this pattern holds up globally. Angela Merkel is barely a blip on Google’s search radar. Worldwide she has never peaked above 1 compared to Trump’s peak score of 100. Perhaps that’s why he refused to shake her hand. Even in Deutschland itself, she peaked at a paltry 17 in the last 5 years against the Trump standard of 100.

Poor Theresa May, the new leader of the United Kingdom, can’t catch a break either. Even on the week she assumed power Donald Trump gained more searches worldwide by a solid 3 to 1 margin.

So let’s put this to the acid test. Trump vs Putin. Worldwide over the past 5 years it was no contest. Trump: 100, Putin: 3 (scored the week of March 2 – 8, 2014, when Putin was making noises about reclaiming Crimea). And yes, even if we restrict the searches to those coming only from Russia, Trump’s best outscored Putin’s best (in June of 2013) by a margin of 2 to 1.

This probably shouldn’t surprise me. According to Google, Donald Trump outscored everyone when it came to searches in 2016. In fact, he came third on Google’s list of most popular searches of any kind, just after Pokémon Go and iPhone 7. The world is locked in a morbid fascination with all that is Trump.

I’d love to wrap up this column with something philosophical and enlightened. It would be good to pass on some tidbit of behavioral wisdom that would put all this search activity into perspective. But that’s not going to happen. All I know is that I’m as guilty as anyone. Since November 8, I search almost daily for ‘Trump” just to see what the last 24 hours hath wrought. I call it my Daily WTF Round Up.

Apparently I’m not alone.

Damn You Technology…

Quit batting your seductive visual sensors at me. You know I can’t resist. But I often wonder what I’m giving up when I give in to your temptations. That’s why I was interested in reading Tom Goodwin’s take on the major theme at SXSW – the Battle for Humanity. He broke this down into three sub themes. I agree with them. In fact, I’ve written on all of them in the past. They were:

Data Trading – We’re creating a market for data. But when you’re the one that generated that data, who should own it?

Shift to No Screens – an increasing number of connected devices will change of concept of what it means to be online.

Content Tunnel Vision – As the content we see is increasingly filtered based on our preferences, what does that do for our perception of what is real?

But while we’re talking about our imminent surrender to the machines, I feel there are some other themes that also merit some discussion. Let’s limit it to two today.

A New Definition of Connection and Community

sapolsky

Robert Sapolsky

A few weeks ago I read an article that I found fascinating by neuroendocrinologist and author Robert Sapolsky. In it, he posits that understanding Capgras Syndrome is the key to understanding the Facebook society. Capgras, first identified by French psychiatrist Joseph Capgras, is a disorder where we can recognize a face of a person but we can’t retrieve feelings of familiarity. Those afflicted can identify the face of a loved one but swear that it’s actually an identical imposter. Recognition of a person and retrieval of emotions attached to that person are handled by two different parts of the brain. When the connection is broken, Capgras Syndrome is the result.

This bifurcation of how we identify people is interesting. There is the yin and yang of cognition and emotion. The fusiform gyrus cognitively “parses” the face and then the brain retrieves the emotions and memories that are associated with it. To a normally functioning brain, it seems seamless and connected, but because two different regions (or, in the case of emotion, a network of regions) are involved, they can neurologically evolve independently of each other. And in the age of Facebook, that could mean a significant shift in the way we recognize connections and create “cognitive communities.” Sapolsky elaborates:

Through history, Capgras syndrome has been a cultural mirror of a dissociative mind, where thoughts of recognition and feelings of intimacy have been sundered. It is still that mirror. Today we think that what is false and artificial in the world around us is substantive and meaningful. It’s not that loved ones and friends are mistaken for simulations, but that simulations are mistaken for them.

As I said in a column a few months back, we are substituting surface cues for familiarity. We are rushing into intimacy without all the messy, time consuming process of understanding and shared experience that generally accompanies it.

Brains do love to take short cuts. They’re not big on heavy lifting. Here’s another example of that…

Free Will is Replaced with An Algorithm

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Yuval Harari

In a conversation with historian Yuval Harari, author of the best seller Sapiens, Derek Thompson from the Atlantic explored “The Post Human World.” One of the topics they discussed was the End of Individualism.

Humans (or, at least, most humans) have believed our decisions come from a mystical soul – a transcendental something that lives above our base biology and is in control of our will. Wrapped up in this is the concept of us as an individual and our importance in the world as free thinking agents.

In the past few decades, there is a growing realization that our notion of “free will” is just the result of a cascade of biochemical processes. There is nothing magical here; there is just a chain of synaptic switches being thrown. And that being the case – if a computer can process things faster than our brains, should we simply relegate our thinking to a machine?

In many ways, this is already happening. We trust Google Maps or our GPS device more than we trust our ability to find our own way. We trust Google Search more than our own memory. We’re on the verge of trusting our wearable fitness tracking devices more than our own body’s feedback. And in all these cases, our trust in tech is justified. These things are usually right more often than we are. But when it comes to humans vs, machines, they represent a slippery slope that we’re already well down. Harari speculates what might be at the bottom:

What really happens is that the self disintegrates. It’s not that you understand your true self better, but you come to realize there is no true self. There is just a complicated connection of biochemical connections, without a core. There is no authentic voice that lives inside you.

When I lay awake worrying about technology, these are the types of things that I think about. The big question is – is humanity an outmoded model? The fact is that we evolved to be successful in a certain environment. But here’s the irony in that: we were so successful that we changed that environment to one where it was the tools we’ve created, not the creators, which are the most successful adaptation. We may have made ourselves obsolete. And that’s why really smart humans, like Bill Gates, Elon Musk and Stephen Hawking are so worried about artificial intelligence.

“It would take off on its own, and re-design itself at an ever increasing rate,” said Hawking in a recent interview with BBC. “Humans, who are limited by slow biological evolution, couldn’t compete, and would be superseded.”

Worried about a machine taking your job? That may be the least of your worries.

 

 

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.

sensemaking2

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.

 

 

 

 

 

 

 

What Comes After Generation Z?

We’re running out of alphabet.

The latest generation is Generation Z. They were born between 1995 and 2012 – according to one demographic primer. So, what do we call the generation born from 2013 on? Z+One? Do we go with an Excel naming scheme and call it Generation AA? Or should we just go back to all those unused letters of the alphabet. After all, we haven’t touched A to W yet. Thinking along those lines, Australian social researcher and author Mark McCrindle is lobbying for Generation Alpha. It’s a nice twist – we get to recycle the alphabet and give it a Greek flavor all at the same time.

Maybe the reason we short-sightedly started with the last three letters of the alphabet is that we’re pretty new at this. Before the twentieth century, we didn’t worry much about labeling every generation. And, to be honest, much of that labeling has happened retroactively. The Silent Generation (1925 – 1942) didn’t call themselves that right off that bat. Being Silent, they didn’t call themselves anything. The label wasn’t coined until 1951. And the G.I. Generation, who preceded them ((1901 – 1924), didn’t receive their label until demographers William Strauss and Neil Howe affixed it in 1991.

But starting around the middle of the last century, we developed the need to pigeonhole our cohorts. Maybe it’s because things started moving so quickly about that time. In the first half of the century we had the twin demographical tent poles of the two World Wars. In between we had the Great Depression. After WWII we had the mother of all generational events: the Baby Boom. Each of these eras brought a very different environment, which would naturally affect those growing up in them. Since then, we’ve been scrambling madly to keep up with appropriate labels for each generation.

The standard approach up to now has been to wait for someone to write a book about a generation, which bestows the label, and then we all jump on the bandwagon. But this seems reactive and short sighted. It also means that we get caught in our current situation, where we have a generation that remains unnamed while we’re waiting for the book to be written.

We seem hooked on these generation labels. I don’t think they’re going to go anywhere any time soon. Based on our current fascination with Millennials, we in the media are going to continue to lump every single sociological and technological trend into convenient generationally labeled behavioral buckets. So we should give this naming thing some thought.

Maybe we could take a page from the World Meteorological Organization’s book when it comes to naming hurricanes and tropical storms. They started doing this so the media would have a quick and commonly understood reference point when referring to a particular meteorological event. Don’t generations deserve the same foresight?

The World Meteorological Organization has a strict procedure: “For Atlantic hurricanes, there is a list of male and female names which are used on a six-year rotation. The only time that there is a change is if a storm is so deadly or costly that the future use of its name on a different storm would be inappropriate. In the event that more than twenty-one named tropical cyclones occur in a season, any additional storms will take names from the Greek alphabet.”

I like the idea of using male and female names. This got me thinking. Maybe we combine the WMO’s approach and that of the wisdom of crowds. Perhaps the male and female names should be the most popular baby names of that generation. In case you’re wondering, here’s how that would work out:

Silent Generation (1925 – 1942): The Robert and Mary Generation
Baby Boomers I (1946 – 1954): The James and Mary Generation
Baby Boomers II (1955 – 1965): The Michael and Lisa Generation
Generation X (1966 – 1976): The Michael and Jennifer Generation
Millennials (1977 – 1994): The Michael and Jessica Generation
Generation Z (1995 – 2012): The Jacob and Emily Generation
Generation ??? (2013 – Today) – The Emma and Noah Generation

The sharp sighted amongst you will have noticed two problems with this. First, some names are stubbornly popular (I’m talking about you Michael and Mary) and span multiple generations. Secondly, this is a very US-Centric approach. Maybe we need to mix it up globally. For instance, if we tap into the naming zeitgeist of South Korea, that would make the current generation the Seo-yeon and Min-jun Generation.

Of course, all this could be needless worrying. Perhaps those that affixed the Generation Z label knew something we didn’t.